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Letteratura scientifica selezionata sul tema "Separation estimation"

Autore: Grafiati

Pubblicato: 7 luglio 2024

Ultima modifica: 7 luglio 2024

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Articoli di riviste sul tema "Separation estimation"

Pishravian, Arash, and Masoud Reza Aghabozorgi Sahaf. "Application of independent component analysis for speech–music separation using an efficient score function estimation." Journal of Electrical Engineering 63, no. 6 (2012): 380–85. http://dx.doi.org/10.2478/v10187-012-0056-0.

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In this paper speech-music separation using Blind Source Separation is discussed. The separating algorithm is based on the mutual information minimization where the natural gradient algorithm is used for minimization. In order to do that, score function estimation from observation signals (combination of speech and music) samples is needed. The accuracy and the speed of the mentioned estimation will affect on the quality of the separated signals and the processing time of the algorithm. The score function estimation in the presented algorithm is based on Gaussian mixture based kernel density estimation method. The experimental results of the presented algorithm on the speech-music separation and comparing to the separating algorithm which is based on the Minimum Mean Square Error estimator, indicate that it can cause better performance and less processing time

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Xiao, Yingchun, Yang Yang, and Feng Zhu. "A Separation Method for Electromagnetic Radiation Sources of the Same Frequency." Journal of Electromagnetic Engineering and Science 23, no. 6 (2023): 521–29. http://dx.doi.org/10.26866/jees.2023.6.r.197.

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To separate electromagnetic interference sources with an unknown source number, a new separation method is proposed, which includes five key steps: spatial spectrum estimation, source number and direction-of-arrival estimation, mixed matrix estimation, separation matrix estimation, and source signal recovery. A pseudospatial spectrum estimation network based on a convolutional neural network is proposed to estimate the number of electromagnetic radiation sources, their direction of arrival, and the mixing matrix. A new loss function is designed as an optimization criterion for estimating the separation matrix. To ensure generalization, both simulated and measured datasets are used to train the proposed network. Experimental results demonstrate that the proposed separation method outperforms existing source separation techniques in terms of correlation coefficient, root mean square error, and running time. Importantly, it exhibits strong performance in underdetermined cases, as well as in overdetermined or determined cases.

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Asadi, Haniyeh, Mohammad T. Dastorani, Roy C. Sidle, and Kaka Shahedi. "Improving Flow Discharge-Suspended Sediment Relations: Intelligent Algorithms versus Data Separation." Water 13, no. 24 (2021): 3650. http://dx.doi.org/10.3390/w13243650.

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Information on the transport of fluvial suspended sediment loads (SSL) is crucial due to its effects on water quality, pollutant transport and transformation, dam operations, and reservoir capacity. As such, adopting a reliable method to accurately estimate SSL is a key topic for watershed managers, hydrologists, river engineers, and hydraulic engineers. One of the most common methods for estimating SSL or suspended sediment concentrations (SSC) is sediment rating curve (SRC), which has several weaknesses. Here, we optimize the SRC equation using two main approaches. Firstly, three well recognized metaheuristic algorithms (genetic algorithm (GA), particle swarm optimization (PSO), and imperialist competitive algorithm (ICA)) were used together with two classical approaches (food and agriculture organization (FAO) and non-parametric smearing estimator (CF2)) to optimize the coefficients of the SRC regression model. The second approach uses separation of data based on season and flow discharge (Qw) characteristics. A support vector regression (SVR) model using only Qw as an input was employed for SSC estimation and the results were compared with the SRC and its optimized versions. Metaheuristic algorithms improved the performance of the SRC model and the PSO model outperformed the other algorithms. These results also indicate that the model performance was directly related to the temporal separation of data. Based on these findings, if data are more homogenous and related to the limited climatic conditions used in the estimation of SSC, the estimations are improved. Moreover, it was observed that optimizing SRC through metaheuristic models was much more effective than separating data in the SCR model. The results also indicated that with the same input data, SVR was superior to the SRC model and its optimized version.

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Todorovic-Zarkula, Slavica, Branimir Todorovic, and Miomir Stankovic. "On-line blind separation of non-stationary signals." Yugoslav Journal of Operations Research 15, no. 1 (2005): 79–95. http://dx.doi.org/10.2298/yjor0501079t.

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This paper addresses the problem of blind separation of non-stationary signals. We introduce an on-line separating algorithm for estimation of independent source signals using the assumption of non-stationary of sources. As a separating model, we apply a self-organizing neural network with lateral connections, and define a contrast function based on correlation of the network outputs. A separating algorithm for adaptation of the network weights is derived using the state-space model of the network dynamics, and the extended Kalman filter. Simulation results obtained in blind separation of artificial and real-world signals from their artificial mixtures have shown that separating algorithm based on the extended Kalman filter outperforms stochastic gradient based algorithm both in convergence speed and estimation accuracy.

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Yang, Xiao Yan, Xiong Zhou, and Yi Ke Tang. "A New Method for Adaptive Blind Source Separation Based on the Estimated Number of Dynamic Fault Sources." Applied Mechanics and Materials 233 (November 2012): 211–17. http://dx.doi.org/10.4028/www.scientific.net/amm.233.211.

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In fault diagnosis of large rotating machinery, the number of fault sources may be subject to dynamic changes, which often lead to the failure in accurate estimation of the number of sources and the effective isolation of the fault source. This paper introduced the expansion of the fourth-order cumulant matrices in estimating the dynamic fault source number, plus the relationship between the source signal number and the number of sensors being utilized in the selection of the blind source separation algorithm to achieve adaptive blind source separation. Experiments showed that the source number estimation algorithm could be quite effective in estimating the dynamic number of fault sources, even in the underdetermined condition. This adaptive blind source separation algorithm could then effectively achieve fault diagnosis in respect to the positive-determined, overdetermined and underdetermined blind source separation.

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Hasegawa, Yasuhisa, Mayumi Natsui, Chie Abe, Ayumi Ikeda, and Sean-Thomas B. Lundin. "Estimation of CO2 Separation Performances through CHA-Type Zeolite Membranes Using Molecular Simulation." Membranes 13, no. 1 (2023): 60. http://dx.doi.org/10.3390/membranes13010060.

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Chabazite (CHA)-type zeolite membranes are a potential material for CO2 separations because of their small pore aperture, large pore volume, and low aluminum content. In this study, the permeation and separation properties were evaluated using a molecular simulation technique with a focus on improving the CO2 separation performance. The adsorption isotherms of CO2 and CH4 on CHA-type zeolite with Si/Al = 18.2 were predicted by grand canonical Monte Carlo, and the diffusivities in zeolite micropores were simulated by molecular dynamics. The CO2 separation performance of the CHA-type zeolite membrane was estimated by a Maxwell–Stefan equation, accounting for mass transfer through the support tube. The results indicated that the permeances of CO2 and CH4 were influenced mainly by the porosity of the support, with the CO2 permeance reduced due to preferential adsorption with increasing pressure drop. In contrast, it was important for estimation of the CH4 permeance to predict the amounts of adsorbed CH4. Using molecular simulation and the Maxwell–Stefan equation is shown to be a useful technique for estimating the permeation properties of zeolite membranes, although some problems such as predicting accurate adsorption terms remain.

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Lui, Hoi-Shun, and Hon Tat Hui. "Direction-of-Arrival Estimation of Closely Spaced Emitters Using Compact Arrays." International Journal of Antennas and Propagation 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/104848.

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Performance evaluation of direction-of-arrival (DOA) estimation algorithms has continuously drawn significant attention in the past years. Most previous studies were conducted under the situation that antenna element separation is about half wavelength in order to avoid the appearance of grating lobes. On the other hand, recent developments in wireless communications have favoured the use of portable devices that utilize compact arrays with antenna element separations of less than half wavelength. Performance evaluation of DOA estimation algorithms employing compact arrays is an important and fundamental issue, but it has not been fully studied. In this paper, the performance of the matrix pencil method (MPM) that applies to DOA estimations is investigated through Monte Carlo simulations. The results show that closely spaced emitters can be accurately resolved using linear compact array with an array aperture as small as around half wavelength.

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Yokoi, Masayuki, and Takao Tashiro. "Separating Prescription From Dispensation Medicines: Economic Effect Estimation in Japan." Global Journal of Health Science 10, no. 5 (2018): 88. http://dx.doi.org/10.5539/gjhs.v10n5p88.

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This study examined the effects of the separation between dispensing and prescribing medicines by pharmacists in pharmacies and doctors in medical institutions, respectively (separation system). The methodology avails public national data. The participation of Japanese medical institutions to the separation system was optional according to the legal system. Consequently, its spreading rate for each administrative district is highly variable, allowing us to study its correlation with various medication costs and other factors, such as the generic medicine replacement ratio, proportion of elderly, and number of doctors per 100 000 individuals as independent variables. These four factors are known to be influential in medical compensation. We used regression analysis by the weighted least square method, with dependent variables being costs of daily medicines, specifically, total, internal, one-shot, external, and injection medicines; medical devices, brand-name medicines, generic medicines, and number of prescribed medicines; as well as technical fees. The analysis focused on whether the extent of the separation system reduces costs such as those for medicines, medical devices, technical fees, or number of prescribed medicines. The partial regression coefficient of the spreading rate of the separation system was found to have negative relationships with all daily costs and number of prescribed medicines, as well as the technical fee, except for external medicines, for which most of the market is represented by light analgesics (taken by patients as needed). The necessity of separating prescribing and dispensing is thus low because of the low information asymmetry between doctors and patients. The results revealed that promoting the separation system reduced medication costs, because it normalized the medication market for daily necessities by compensating information asymmetry. Furthermore, the separation system reduced excesses in prescribing medicines.

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Reddy, Priyanka J., Vandana Pulhani, Sanjay D. Dhole, Shailesh S. Dahiwale, Sonali P. D. Bhade, and Devendra D. Rao. "Sequential analysis of uranium and plutonium in environmental matrices by extractive liquid scintillation spectrometry." Radiochimica Acta 106, no. 10 (2018): 809–18. http://dx.doi.org/10.1515/ract-2017-2916.

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Abstract A methodology for sequential separation of uranium (U) and plutonium (Pu) followed by their estimation, using extractive liquid scintillation spectrometry was standardized for matrices like soil, fish and sediment. Various parameters for selective and efficient extraction and separation of Pu and U in the presence of interfering matrix elements with HDEHP bis(2-ethylhexy1) phosphoric acid as an extracting agent were investigated. Quenching effect of the various extracting reagents on resolution of α spectrum of analytes and reduction in these interferences is discussed in the current study. Standardized procedure gave about 91% of extraction of spiked Pu into the organic phase. Performance of the method was tested by separating and estimating U and Pu in International Atomic Agency (IAEA) certified reference materials like soil/sediment/fish.

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Yang, ZuYuan, BeiHai Tan, GuoXu Zhou, and JinLong Zhang. "Source number estimation and separation algorithms of underdetermined blind separation." Science in China Series F: Information Sciences 51, no. 10 (2008): 1623–32. http://dx.doi.org/10.1007/s11432-008-0138-6.

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Più fonti

Tesi sul tema "Separation estimation"

Gunawan, David Oon Tao Electrical Engineering &amp Telecommunications Faculty of Engineering UNSW. "Musical instrument sound source separation." Awarded By:University of New South Wales. Electrical Engineering & Telecommunications, 2009. http://handle.unsw.edu.au/1959.4/41751.

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The structured arrangement of sounds in musical pieces, results in the unique creation of complex acoustic mixtures. The analysis of these mixtures, with the objective of estimating the individual sounds which constitute them, is known as musical instrument sound source separation, and has applications in audio coding, audio restoration, music production, music information retrieval and music education. This thesis principally addresses the issues related to the separation of harmonic musical instrument sound sources in single-channel mixtures. The contributions presented in this work include novel separation methods which exploit the characteristic structure and inherent correlations of pitched sound sources; as well as an exploration of the musical timbre space, for the development of an objective distortion metric to evaluate the perceptual quality of separated sources. The separation methods presented in this work address the concordant nature of musical mixtures using a model-based paradigm. Model parameters are estimated for each source, beginning with a novel, computationally efficient algorithm for the refinement of frequency estimates of the detected harmonics. Harmonic tracks are formed, and overlapping components are resolved by exploiting spectro-temporal intra-instrument dependencies, integrating the spectral and temporal approaches which are currently employed in a mutually exclusive manner in existing systems. Subsequent to the harmonic magnitude extraction using this method, a unique, closed-loop approach to source synthesis is presented, separating sources by iteratively minimizing the aggregate error of the sources, constraining the minimization to a set of estimated parameters. The proposed methods are evaluated independently, and then are placed within the context of a source separation system, which is evaluated using objective and subjective measures. The evaluation of music source separation systems is presently limited by the simplicity of objective measures, and the extensive effort required to conduct subjective evaluations. To contribute to the development of perceptually relevant evaluations, three psychoacoustic experiments are also presented, exploring the perceptual sensitivity of timbre for the development of an objective distortion metric for timbre. The experiments investigate spectral envelope sensitivity, spectral envelope morphing and noise sensitivity.

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Parfitt, Maxwell. "Estimation of magnet separation for magnetic suspension applications." Thesis, University of Reading, 2013. http://centaur.reading.ac.uk/36656/.

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This thesis describes a form of non-contact measurement using two dimensional hall effect sensing to resolve the location of a moving magnet which is part of a ‘magnetic spring’ type suspension system. This work was inspired by the field of Space Robotics, which currently relies on solid link suspension techniques for rover stability. This thesis details the design, development and testing of a novel magnetic suspension system with a possible application in space and terrestrial based robotics, especially when the robot needs to traverse rough terrain. A number of algorithms were developed, to utilize experimental data from testing, that can approximate the separation between magnets in the suspension module through observation of the magnetic fields. Experimental hardware was also developed to demonstrate how two dimensional hall effect sensor arrays could provide accurate feedback, with respects to the magnetic suspension modules operation, so that future work can include the sensor array in a real-time control system to produce dynamic ride control for space robots. The research performed has proven that two dimensional hall effect sensing with respects to magnetic suspension is accurate, effective and suitable for future testing.

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Che, Viet Nhat Anh. "Cyclostationary analysis : cycle frequency estimation and source separation." Thesis, Saint-Etienne, 2011. http://www.theses.fr/2011STET4035.

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Le problème de séparation aveugle de sources a but de retrouver un ensemble des sources signaux statistiquement indépendants à partir seulement d’un ensemble des observations du capteur. Ces observations peuvent être modélisées comme un mélanges linéaires instantané ou convolutifs de sources. Dans cette thèse, les sources signaux sont supposées être cyclostationnaire où leurs fréquences cycles peuvent être connues ou inconnu par avance. Premièrement, nous avons établi des relations entre le spectre, spectre de puissance d’un signal source et leurs composants, puis nous avons proposé deux nouveaux algorithmes pour estimer sa fréquences cycliques. Ensuite, pour la séparation aveugle de sources en mélanges instantanés, nous présentons quatre algorithmes basés sur diagonalisation conjoint approchées orthogonale (ou non-orthogonales) d’une famille des matrices cycliques multiples moment temporel, or l’approche matricielle crayon pour extraire les sources signaux. Nous introduisons aussi et prouver une nouvelle condition identifiabilité pour montrer quel type de sources cyclostationnaires d’entrée peuvent être séparées basées sur des statistiques cyclostationnarité à l’ordre deux. Pour la séparation aveugle de sources en mélanges convolutifs, nous présentons un algorithme en deux étapes basées sur une approche dans le domaine temporel pour récupérer les signaux source. Les simulations numériques sont utilisés dans cette thèse pour démontrer l’efficacité de nos approches proposées, et de comparer les performances avec leurs méthodes précédentes<br>Blind source separation problem aims to recover a set of statistically independent source signals from a set of sensor observations. These observations can be modeled as an instantaneous or convolutive mixture of the same sources. In this dissertation, the source signals are assumed to be cyclostationary where their cycle frequencies may be known or unknown a priori. First, we establish relations between the spectrum, power spectrum of a source signal and its component, then we propose two novel algorithms to estimate its cycle frequencies. Next, for blind separation of instantaneous mixtures of sources, we present four algorithms based on orthogonal (or non-orthogonal) approximate diagonalization of the multiple cyclic temporal moment matrices, and the matrix pencil approach to extract the source signal. We also introduce and prove a new identifiability condition to show which kind of input cyclostationary sources can be separated based on second-order cyclostationarity statistics. For blind separation of convolutive mixtures of sources signal or blind deconvolution of FIR MIMO systems, we present a two-steps algorithm based on time domain approach for recovering the source signals. Numerical simulations are used throughout this thesis to demonstrate the effectiveness of our proposed approaches, and compare theirs performances with previous methods

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Meseguer, Brocal Gabriel. "Multimodal analysis : informed content estimation and audio source separation." Electronic Thesis or Diss., Sorbonne université, 2020. http://www.theses.fr/2020SORUS111.

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Cette thèse propose l'étude de l'apprentissage multimodal dans le contexte de signaux musicaux. Tout au long de ce manuscrit, nous nous concentrerons sur l'interaction entre les signaux audio et les informations textuelles. Parmi les nombreuses sources de texte liées à la musique qui peuvent être utilisées (par exemple les critiques, les métadonnées ou les commentaires des réseaux sociaux), nous nous concentrerons sur les paroles. La voix chantée relie directement le signal audio et les informations textuelles d'une manière unique, combinant mélodie et paroles où une dimension linguistique complète l'abstraction des instruments de musique. Notre étude se focalise sur l'interaction audio et paroles pour cibler la séparation de sources et l'estimation de contenu informé. Les stimuli du monde réel sont produits par des phénomènes complexes et leur interaction constante dans divers domaines. Notre compréhension apprend des abstractions utiles qui fusionnent différentes modalités en une représentation conjointe. L'apprentissage multimodal décrit des méthodes qui analysent les phénomènes de différentes modalités et leur interaction afin de s'attaquer à des tâches complexes. Il en résulte des représentations meilleures et plus riches qui améliorent les performances des méthodes d'apprentissage automatique actuelles. Pour développer notre analyse multimodale, nous devons d'abord remédier au manque de données contenant une voix chantée avec des paroles alignées. Ces données sont obligatoires pour développer nos idées. Par conséquent, nous étudierons comment créer une telle base de données en exploitant automatiquement les ressources du World Wide Web. La création de ce type de base de données est un défi en soi qui soulève de nombreuses questions de recherche. Nous travaillons constamment avec le paradoxe classique de la `` poule ou de l'œuf '': l'acquisition et le nettoyage de ces données nécessitent des modèles précis, mais il est difficile de former des modèles sans données. Nous proposons d'utiliser le paradigme enseignant-élève pour développer une méthode où la création de bases de données et l'apprentissage de modèles ne sont pas considérés comme des tâches indépendantes mais plutôt comme des efforts complémentaires. Dans ce processus, les paroles et les annotations non-expertes de karaoké décrivent les paroles comme une séquence de notes alignées sur le temps avec leurs informations textuelles associées. Nous lions ensuite chaque annotation à l'audio correct et alignons globalement les annotations dessus<br>This dissertation proposes the study of multimodal learning in the context of musical signals. Throughout, we focus on the interaction between audio signals and text information. Among the many text sources related to music that can be used (e.g. reviews, metadata, or social network feedback), we concentrate on lyrics. The singing voice directly connects the audio signal and the text information in a unique way, combining melody and lyrics where a linguistic dimension complements the abstraction of musical instruments. Our study focuses on the audio and lyrics interaction for targeting source separation and informed content estimation. Real-world stimuli are produced by complex phenomena and their constant interaction in various domains. Our understanding learns useful abstractions that fuse different modalities into a joint representation. Multimodal learning describes methods that analyse phenomena from different modalities and their interaction in order to tackle complex tasks. This results in better and richer representations that improve the performance of the current machine learning methods. To develop our multimodal analysis, we need first to address the lack of data containing singing voice with aligned lyrics. This data is mandatory to develop our ideas. Therefore, we investigate how to create such a dataset automatically leveraging resources from the World Wide Web. Creating this type of dataset is a challenge in itself that raises many research questions. We are constantly working with the classic ``chicken or the egg'' problem: acquiring and cleaning this data requires accurate models, but it is difficult to train models without data. We propose to use the teacher-student paradigm to develop a method where dataset creation and model learning are not seen as independent tasks but rather as complementary efforts. In this process, non-expert karaoke time-aligned lyrics and notes describe the lyrics as a sequence of time-aligned notes with their associated textual information. We then link each annotation to the correct audio and globally align the annotations to it. For this purpose, we use the normalized cross-correlation between the voice annotation sequence and the singing voice probability vector automatically, which is obtained using a deep convolutional neural network. Using the collected data we progressively improve that model. Every time we have an improved version, we can in turn correct and enhance the data

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Lahlou, Mouncef. "Color-Based Surface Reflectance Separation for Scene Illumination Estimation and Rendering." FIU Digital Commons, 2011. http://digitalcommons.fiu.edu/etd/381.

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Given the importance of color processing in computer vision and computer graphics, estimating and rendering illumination spectral reflectance of image scenes is important to advance the capability of a large class of applications such as scene reconstruction, rendering, surface segmentation, object recognition, and reflectance estimation. Consequently, this dissertation proposes effective methods for reflection components separation and rendering in single scene images. Based on the dichromatic reflectance model, a novel decomposition technique, named the Mean-Shift Decomposition (MSD) method, is introduced to separate the specular from diffuse reflectance components. This technique provides a direct access to surface shape information through diffuse shading pixel isolation. More importantly, this process does not require any local color segmentation process, which differs from the traditional methods that operate by aggregating color information along each image plane. Exploiting the merits of the MSD method, a scene illumination rendering technique is designed to estimate the relative contributing specular reflectance attributes of a scene image. The image feature subset targeted provides a direct access to the surface illumination information, while a newly introduced efficient rendering method reshapes the dynamic range distribution of the specular reflectance components over each image color channel. This image enhancement technique renders the scene illumination reflection effectively without altering the scene’s surface diffuse attributes contributing to realistic rendering effects. As an ancillary contribution, an effective color constancy algorithm based on the dichromatic reflectance model was also developed. This algorithm selects image highlights in order to extract the prominent surface reflectance that reproduces the exact illumination chromaticity. This evaluation is presented using a novel voting scheme technique based on histogram analysis. In each of the three main contributions, empirical evaluations were performed on synthetic and real-world image scenes taken from three different color image datasets. The experimental results show over 90% accuracy in illumination estimation contributing to near real world illumination rendering effects.

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Becker, Saskia. "The Propagation-Separation Approach." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2014. http://dx.doi.org/10.18452/16960.

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Lokal parametrische Modelle werden häufig im Kontext der nichtparametrischen Schätzung verwendet. Bei einer punktweisen Schätzung der Zielfunktion können die parametrischen Umgebungen mithilfe von Gewichten beschrieben werden, die entweder von den Designpunkten oder (zusätzlich) von den Beobachtungen abhängen. Der Vergleich von verrauschten Beobachtungen in einzelnen Punkten leidet allerdings unter einem Mangel an Robustheit. Der Propagations-Separations-Ansatz von Polzehl und Spokoiny [2006] verwendet daher einen Multiskalen-Ansatz mit iterativ aktualisierten Gewichten. Wir präsentieren hier eine theoretische Studie und numerische Resultate, die ein besseres Verständnis des Verfahrens ermöglichen. Zu diesem Zweck definieren und untersuchen wir eine neue Strategie für die Wahl des entscheidenden Parameters des Verfahrens, der Adaptationsbandweite. Insbesondere untersuchen wir ihre Variabilität in Abhängigkeit von der unbekannten Zielfunktion. Unsere Resultate rechtfertigen eine Wahl, die unabhängig von den jeweils vorliegenden Beobachtungen ist. Die neue Parameterwahl liefert für stückweise konstante und stückweise beschränkte Funktionen theoretische Beweise der Haupteigenschaften des Algorithmus. Für den Fall eines falsch spezifizierten Modells führen wir eine spezielle Stufenfunktion ein und weisen eine punktweise Fehlerschranke im Vergleich zum Schätzer des Algorithmus nach. Des Weiteren entwickeln wir eine neue Methode zur Entrauschung von diffusionsgewichteten Magnetresonanzdaten. Unser neues Verfahren (ms)POAS basiert auf einer speziellen Beschreibung der Daten, die eine zeitgleiche Glättung bezüglich der gemessenen Positionen und der Richtungen der verwendeten Diffusionsgradienten ermöglicht. Für den kombinierten Messraum schlagen wir zwei Distanzfunktionen vor, deren Eignung wir mithilfe eines differentialgeometrischen Ansatzes nachweisen. Schließlich demonstrieren wir das große Potential von (ms)POAS auf simulierten und experimentellen Daten.<br>In statistics, nonparametric estimation is often based on local parametric modeling. For pointwise estimation of the target function, the parametric neighborhoods can be described by weights that depend on design points or on observations. As it turned out, the comparison of noisy observations at single points suffers from a lack of robustness. The Propagation-Separation Approach by Polzehl and Spokoiny [2006] overcomes this problem by using a multiscale approach with iteratively updated weights. The method has been successfully applied to a large variety of statistical problems. Here, we present a theoretical study and numerical results, which provide a better understanding of this versatile procedure. For this purpose, we introduce and analyse a novel strategy for the choice of the crucial parameter of the algorithm, namely the adaptation bandwidth. In particular, we study its variability with respect to the unknown target function. This justifies a choice independent of the data at hand. For piecewise constant and piecewise bounded functions, this choice enables theoretical proofs of the main heuristic properties of the algorithm. Additionally, we consider the case of a misspecified model. Here, we introduce a specific step function, and we establish a pointwise error bound between this function and the corresponding estimates of the Propagation-Separation Approach. Finally, we develop a method for the denoising of diffusion-weighted magnetic resonance data, which is based on the Propagation-Separation Approach. Our new procedure, called (ms)POAS, relies on a specific description of the data, which enables simultaneous smoothing in the measured positions and with respect to the directions of the applied diffusion-weighting magnetic field gradients. We define and justify two distance functions on the combined measurement space, where we follow a differential geometric approach. We demonstrate the capability of (ms)POAS on simulated and experimental data.

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Han, Kun. "Supervised Speech Separation And Processing." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1407865723.

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Liu, Yuzhou. "Deep CASA for Robust Pitch Tracking and Speaker Separation." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1566179636974186.

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Umiltà, Caterina. "Development and assessment of a blind component separation method for cosmological parameter estimation." Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066453/document.

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Le rayonnement fossile, ou CMB, est un sujet d’étude clé pour la cosmologie car il indique l’état de l’univers à une époque primordiale. Le CMB est observable dans le ciel dans la bande de fréquences des micro-ondes. Cependant, il existe des processus astrophysiques, les avant-plans, qui émettent dans les micro-ondes, et rendent indispensable le traitement des données avec des méthodes de séparation de composantes. J'utilisé la méthode aveugle SMICA pour obtenir une estimation directe du spectre de puissance angulaire du CMB. La détermination des petites échelles de ce spectre est limité par les avant-plans comme les galaxies lointaines, et par le biais du bruit. Dans cette analyse, ces deux limitations sont abordées. En ajoutant des hypothèses sur la physique des galaxies lointaines, il est possible de guider l’algorithme pour estimer leur loi d'émission. Un spectre de puissance angulaire obtenu d'une carte du ciel a un biais dû au bruit à petites échelles. Toutefois, les spectres obtenus en croisant différentes cartes n'ont pas ce biais. J'ai donc adapté la méthode SMICA pour qu'elle n'utilise que ces derniers, diminuant l'incertitude due au bruit dans l'estimation du CMB. Cette méthode a été étudiée sur des nombreuses simulations et sur les données Planck 2015, afin d'estimer des paramètres cosmologiques. Les résultats montrent que la contamination résiduelle des avant-plans présente dans le spectre CMB, même si fortement réduite, peut introduire des biais dans l'estimation des paramètres si la forme des résiduels n'est pas bien connue. Dans cette thèse, je montre les résultats obtenus en étudiant un modèle de gravité modifiée<br>The Planck satellite observed the whole sky at various frequencies in the microwave range. These data are of high value to cosmology, since they help understanding the primordial universe through the observation of the cosmic microwave background (CMB) signal. To extract the CMB information, astrophysical foreground emissions need to be removed via component separation techniques. In this work I use the blind component separation method SMICA to estimate the CMB angular power spectrum with the aim of using it for the estimation of cosmological parameters. In order to do so, small scales limitations as the residual contamination of unresolved point sources and the noise need to be addressed. In particular, the point sources are modelled as two independent populations with a flat angular power spectrum: by adding this information, the SMICA method is able to recover the joint emission law of point sources. Auto-spectra deriving from one sky map have a noise bias at small scales, while cross-spectra show no such bias. This is particularly true in the case of cross-spectra between data-splits, corresponding to sky maps with the same astrophysical content but different noise properties. I thus adapt SMICA to use data-split cross-spectra only. The obtained CMB spectra from simulations and Planck 2015 data are used to estimate cosmological parameters. Results show that this estimation can be biased if the shape of the (weak) foreground residuals in the angular power spectrum is not well known. In the end, I also present results of the study of a Modified Gravity model called Induced Gravity

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Landqvist, Ronnie. "Signal processing techniques in mobile communication systems : signal separation, channel estimation and equalization /." Karlskrona : Blekinge Institute of Technology, 2005. http://www.bth.se/fou/Forskinfo.nsf/allfirst2/98bf8bfb44d67d86c1257099003e2fc1?OpenDocument.

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Libri sul tema "Separation estimation"

Vergouw, Ir Jolanda. A conductivity probe for thickeners: Calibration and level estimation. s.n.]., 1998.

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Estimation of Supersonic Stage Separation Aerodynamics of Winged-Body Launch Vehicles Using Response Surface Methods. Independently Published, 2020.

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National Aeronautics and Space Administration (NASA) Staff. Estimation of Supersonic Stage Separation Aerodynamics of Winged-Body Launch Vehicles Using Response Surface Methods. Independently Published, 2019.

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Congendo, Marco, and Fernando H. Lopes da Silva. Event-Related Potentials. Edited by Donald L. Schomer and Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0039.

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Event-related potentials (ERPs) can be elicited by a variety of stimuli and events in diverse conditions. This chapter covers the methodology of analyzing and quantifying ERPs in general. Basic models (additive, phase modulation and resetting, potential asymmetry) that account for the generation of ERPs are discussed. The principles and requirements of ensemble time averaging are presented, along with several univariate and multivariate methods that have been proposed to improve the averaging procedure: wavelet decomposition and denoising, spatial, temporal and spatio-temporal filtering. We emphasize basic concepts of principal component analysis, common spatial pattern, and blind source separation, including independent component analysis. We cover practical questions related to the averaging procedure: overlapping ERPs, correcting inter-sweep latency and amplitude variability, alternative averaging methods (e.g., median), and estimation of ERP onset. Some specific aspects of ERP analysis in the frequency domain are surveyed, along with topographic analysis, statistical testing, and classification methods.

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Cardot, Hervé, and Pascal Sarda. Functional Linear Regression. Edited by Frédéric Ferraty and Yves Romain. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199568444.013.2.

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This article presents a selected bibliography on functional linear regression (FLR) and highlights the key contributions from both applied and theoretical points of view. It first defines FLR in the case of a scalar response and shows how its modelization can also be extended to the case of a functional response. It then considers two kinds of estimation procedures for this slope parameter: projection-based estimators in which regularization is performed through dimension reduction, such as functional principal component regression, and penalized least squares estimators that take into account a penalized least squares minimization problem. The article proceeds by discussing the main asymptotic properties separating results on mean square prediction error and results on L2 estimation error. It also describes some related models, including generalized functional linear models and FLR on quantiles, and concludes with a complementary bibliography and some open problems.

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National Aeronautics and Space Administration (NASA) Staff. Separating Direct and Indirect Turbofan Engine Combustion Noise While Estimating Post-Combustion (Post-Flame) Residence Time Using the Correlation Function. Independently Published, 2019.

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Kelly, Phil. Defending Classical Geopolitics. Oxford University Press, 2017. http://dx.doi.org/10.1093/acrefore/9780190228637.013.279.

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Three successive parts are presented within this article, all intended to raise the visibility and show the utility of classical geopolitics as a deserving and separate international-relations model: (a) a common traditional definition, (b) relevant theories that correspond to that definition, and (c) applications of certain theories that will delve at some depth into three case studies (the Ukrainian shatterbelt, contemporary Turkish geopolitics, and a North American heartland).The placement of states, regions, and resources, as affecting international relations and foreign policies, defines classical geopolitics. This definition emphasizes the application of spatially composed unbiased theories that should bring insight into foreign-affairs events and policies. Specifically, a “model” contains theories that correspond to its description. A “theory” is a simple sentence of probability, with “A” happening to likely affect “B.” Importantly, models are passive; they merely hold theories. In contrast, theories possess their own titles and perform actively when taken from such models.Various methodological challenges are presented: (a) combining concepts with theories, (b) estimating probability for testing theories, (c) claiming the “scientific,” (d) accounting for determinism, (e) revealing a dynamic environment for geopolitics, (f) separating realism from geopolitics, and (g) drawing classical geopolitics away from the critical. Certain theories that are placed within the geopolitical model are examined next: (a) heartlands and rimlands, (b) land and sea power, (c) choke points and maritime lines of communication, (d) offshore balancing, (e) the Monroe doctrine, (f) balances of power, (g) checkerboards, (h) shatterbelts, (i) pan-regions, (j) influence spheres, (k) dependency, (l) buffer states, (m) organic borders, (n) imperial thesis, (o) borders/wars, (p) contagion, (q) irredentism, (r) demography, (s) fluvial laws, (t) petro-politics, and (u) catastrophic events in nature. Additional theories apply elsewhere in the article as well.Of the three case studies, the Ukrainian shatterbelt represents the sole contemporary geopolitical configuration of this type, a regional conflict coupling with a strategic rivalry. Here, partisans of the civil war between the eastern and the western sectors of the country have joined with the Russians against the Europeans and Americans, respectively. Next, Turkey’s pivotal location has afforded it both advantages and disadvantages, a topic discussed at some length earlier in the article. Its “zero-problems” strategy of seeking positive relations with neighbors has now been forced to change tactics, reflective of new forces within and beyond the country. Finally, a North American heartland compares nicely to Halford Mackinder’s earlier Eurasia heartland thesis, with the American perhaps proving more stable, wealthy, and enduring, based in large part on its stronger geopolitical features.

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Capitoli di libri sul tema "Separation estimation"

Zarzoso, V., and A. K. Nandi. "Blind Source Separation." In Blind Estimation Using Higher-Order Statistics. Springer US, 1999. http://dx.doi.org/10.1007/978-1-4757-2985-6_4.

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King, M. B., O. J. Catchpole, and T. R. Bott. "Estimation of separation cost." In Extraction of Natural Products Using Near-Critical Solvents. Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-2138-5_10.

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Markovich-Golan, Shmulik, Walter Kellermann, and Sharon Gannot. "Multichannel Parameter Estimation." In Audio Source Separation and Speech Enhancement. John Wiley & Sons Ltd, 2018. http://dx.doi.org/10.1002/9781119279860.ch11.

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Chen, Jitong, and DeLiang Wang. "DNN Based Mask Estimation for Supervised Speech Separation." In Audio Source Separation. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73031-8_9.

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Daei, Sajad, Massoud Babaie-Zadeh, and Christian Jutten. "A MAP-Based Order Estimation Procedure for Sparse Channel Estimation." In Latent Variable Analysis and Signal Separation. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22482-4_40.

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Martínez-Guerra, Rafael, and Christopher Diego Cruz-Ancona. "A Separation Principle for Nonlinear Systems." In Algorithms of Estimation for Nonlinear Systems. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53040-6_9.

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Shaw, Jane E., and P. W. Ramwell. "Separation, Identification, and Estimation of Prostaglandins." In Methods of Biochemical Analysis. John Wiley & Sons, Inc., 2006. http://dx.doi.org/10.1002/9780470110355.ch8.

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Moreau, Eric, and Tülay Adali. "Estimation by Joint Diagonalization." In Blind Identification and Separation of Complex-Valued Signals. John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118579749.ch2.

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Corey, Ryan M., and Andrew C. Singer. "Relative Transfer Function Estimation from Speech Keywords." In Latent Variable Analysis and Signal Separation. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93764-9_23.

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El Badawy, Dalia, Ivan Dokmanić, and Martin Vetterli. "Acoustic DoA Estimation by One Unsophisticated Sensor." In Latent Variable Analysis and Signal Separation. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53547-0_9.

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Atti di convegni sul tema "Separation estimation"

Lacoume, J. L., and M. Gaeta. "The general source separation problem." In Fifth ASSP Workshop on Spectrum Estimation and Modeling. IEEE, 1990. http://dx.doi.org/10.1109/spect.1990.205565.

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Feige, Uriel, and Shlomo Jozeph. "Separation between Estimation and Approximation." In ITCS'15: Innovations in Theoretical Computer Science. ACM, 2015. http://dx.doi.org/10.1145/2688073.2688101.

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Cheng, Wei, Seungchul Lee, Zhousuo Zhang, and Zhengjia He. "Dissimilarity Measures for ICA-Based Source Number Estimation." In ASME 2012 International Manufacturing Science and Engineering Conference collocated with the 40th North American Manufacturing Research Conference and in participation with the International Conference on Tribology Materials and Processing. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/msec2012-7340.

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Most of blind source separation problems are carried out with a priori knowledge of the source numbers. However, for source separation-based machinery condition monitoring and fault diagnosis, it is a challenge work to determine the number of sources for a well source separation due to complex structures and nonlinear mixing mode. Therefore, source number estimation is a necessary and important procedure prior to source separation and further diagnosis work. In this paper, we focus on a novel source number estimation method based on independent component analysis (ICA) and clustering evaluation analysis, and investigate the performances of different dissimilarity measures of ICA-based source number estimations with typical mechanical vibration signals. Our work contributes to find an effective solution of source number estimation for source separation-based machinery condition monitoring and fault diagnosis.

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Dunham, Darin T., and Scott E. August. "Kinematic separation point estimation using PMHT." In 2010 IEEE Aerospace Conference. IEEE, 2010. http://dx.doi.org/10.1109/aero.2010.5446683.

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Jiang, Xiaoyun, and Noboru Ohta. "Maximum color separation in illuminant estimation." In Electronic Imaging 2004, edited by Reiner Eschbach and Gabriel G. Marcu. SPIE, 2003. http://dx.doi.org/10.1117/12.527445.

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Dunham, Darin T., and Scott E. August. "Using PMHT for separation point estimation." In SPIE Defense, Security, and Sensing, edited by Oliver E. Drummond. SPIE, 2010. http://dx.doi.org/10.1117/12.851468.

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Li Jiang, Lin Li, and Guo-qing Zhao. "Pulse-compression radar signal sorting using the blind source separation algrithms." In 2015 International Conference on Estimation, Detection and Information Fusion (ICEDIF). IEEE, 2015. http://dx.doi.org/10.1109/icedif.2015.7280204.

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Dorfan, Yuval, Ofer Schwartz, Boaz Schwartz, Emanuel A. P. Habets, and Sharon Gannot. "Multiple DOA estimation and blind source separation using estimation-maximization." In 2016 IEEE International Conference on the Science of Electrical Engineering (ICSEE). IEEE, 2016. http://dx.doi.org/10.1109/icsee.2016.7806066.

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Stephenson, Cory, Patrick Callier, Abhinav Ganesh, and Karl Ni. "Monaural speaker separation using source-contrastive estimation." In 2017 IEEE International Workshop on Signal Processing Systems (SiPS). IEEE, 2017. http://dx.doi.org/10.1109/sips.2017.8110005.

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Karbancioglu, Ibrahim Murat, Gökmen Mahmutyazicioglu, and Kemal Ozgoren. "Estimation of Separation Aerodynamics Using Photogrammetric Data." In AIAA Atmospheric Flight Mechanics Conference. American Institute of Aeronautics and Astronautics, 2010. http://dx.doi.org/10.2514/6.2010-7952.

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Rapporti di organizzazioni sul tema "Separation estimation"

Searcy, Stephen W., and Kalman Peleg. Adaptive Sorting of Fresh Produce. United States Department of Agriculture, 1993. http://dx.doi.org/10.32747/1993.7568747.bard.

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This project includes two main parts: Development of a “Selective Wavelength Imaging Sensor” and an “Adaptive Classifiery System” for adaptive imaging and sorting of agricultural products respectively. Three different technologies were investigated for building a selectable wavelength imaging sensor: diffraction gratings, tunable filters and linear variable filters. Each technology was analyzed and evaluated as the basis for implementing the adaptive sensor. Acousto optic tunable filters were found to be most suitable for the selective wavelength imaging sensor. Consequently, a selectable wavelength imaging sensor was constructed and tested using the selected technology. The sensor was tested and algorithms for multispectral image acquisition were developed. A high speed inspection system for fresh-market carrots was built and tested. It was shown that a combination of efficient parallel processing of a DSP and a PC based host CPU in conjunction with a hierarchical classification system, yielded an inspection system capable of handling 2 carrots per second with a classification accuracy of more than 90%. The adaptive sorting technique was extensively investigated and conclusively demonstrated to reduce misclassification rates in comparison to conventional non-adaptive sorting. The adaptive classifier algorithm was modeled and reduced to a series of modules that can be added to any existing produce sorting machine. A simulation of the entire process was created in Matlab using a graphical user interface technique to promote the accessibility of the difficult theoretical subjects. Typical Grade classifiers based on k-Nearest Neighbor techniques and linear discriminants were implemented. The sample histogram, estimating the cumulative distribution function (CDF), was chosen as a characterizing feature of prototype populations, whereby the Kolmogorov-Smirnov statistic was employed as a population classifier. Simulations were run on artificial data with two-dimensions, four populations and three classes. A quantitative analysis of the adaptive classifier's dependence on population separation, training set size, and stack length determined optimal values for the different parameters involved. The technique was also applied to a real produce sorting problem, e.g. an automatic machine for sorting dates by machine vision in an Israeli date packinghouse. Extensive simulations were run on actual sorting data of dates collected over a 4 month period. In all cases, the results showed a clear reduction in classification error by using the adaptive technique versus non-adaptive sorting.

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Ferguson, Thomas, and Servaas Storm. Trump versus Biden: The Macroeconomics of the Second Coming. Institute for New Economic Thinking Working Paper Series, 2024. http://dx.doi.org/10.36687/inetwp221.

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The wafer-thin poll margins separating President Joe Biden and Donald Trump have surprised and baffled many analysts. This paper attempts no analysis of the election itself. It focuses instead on a clinical assessment of its macroeconomic context. Building on previous work, this paper looks first at inflation’s overall effect on real wages and salaries. It then considers claims advanced by Autor, Dube and McGrew (2023) and others about wages of the lowest paid workers. Real wages for most American workers have declined substantially under inflation. We observe no sign of a radical transformation of the U.S. labor market in favor of the lowest-paid workers. The (modest) increase in real hourly wages of the bottom 10% of U.S. workers during 2021-2023 owed little to any policy change or declining monopsony power: It was a unique case of wages rising to subsistence levels as COVID exponentially multiplied risks of working at what had previously been relatively safe jobs at the bottom of the wage distribution. The paper then analyzes inflation’s persistence in the face of substantial increases in interest rates. We document the wealth gains made by the richest 10% of U.S. households during 2020-2023. These wealth gains, which have no peacetime precedents, enabled the richest American households to step up consumption, even when their real incomes were falling. Empirically plausible estimations of the wealth effect on the consumption of the super-rich show that the wealth effect can account for all of the increase in aggregate consumption spending above its longer-term trend during 2021Q1-2023Q4. Importantly, the lopsided inequality in wealth makes controlling lopsided consumption spending by raising interest rates much harder for the Federal Reserve, without interest rate increases that would bring the rest of the economy to its knees much earlier. We also show that the persistence of inflation in several key service sectors is heavily influenced by captive regulators – a condition that higher interest rates cannot remedy.

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Equipment Design and Cost Estimation for Small Modular Biomass Systems, Synthesis Gas Cleanup, and Oxygen Separation Equipment; Task 2.3: Sulfur Primer. Office of Scientific and Technical Information (OSTI), 2006. http://dx.doi.org/10.2172/882502.

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Equipment Design and Cost Estimation for Small Modular Biomass Systems, Synthesis Gas Cleanup, and Oxygen Separation Equipment; Task 1: Cost Estimates of Small Modular Systems. Office of Scientific and Technical Information (OSTI), 2006. http://dx.doi.org/10.2172/882499.

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Equipment Design and Cost Estimation for Small Modular Biomass Systems, Synthesis Gas Cleanup, and Oxygen Separation Equipment; Task 9: Mixed Alcohols From Syngas -- State of Technology. Office of Scientific and Technical Information (OSTI), 2006. http://dx.doi.org/10.2172/882503.

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Equipment Design and Cost Estimation for Small Modular Biomass Systems, Synthesis Gas Cleanup, and Oxygen Separation Equipment; Task 2: Gas Cleanup Design and Cost Estimates -- Wood Feedstock. Office of Scientific and Technical Information (OSTI), 2006. http://dx.doi.org/10.2172/882500.

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Equipment Design and Cost Estimation for Small Modular Biomass Systems, Synthesis Gas Cleanup, and Oxygen Separation Equipment; Task 2: Gas Cleanup Design and Cost Estimates -- Black Liquor Gasification. Office of Scientific and Technical Information (OSTI), 2006. http://dx.doi.org/10.2172/882504.

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