Artículos de revistas: "Filtros de Savitzky-Golay"

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Melo Junior, Gilberto de, Sílvio Leão Vieira, Geovanne Pereira Furriel, Renato Milhomem de Oliveira Filho, Brunna Carolinne Rocha Silva y Jane Sousa Naves. "Pré-processamento de sinais Eletro-oculográficos (EOG)". Research, Society and Development 10, n.º 4 (10 de abril de 2021): e28410414221. http://dx.doi.org/10.33448/rsd-v10i4.14221.

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Este trabalho visa estudar sinais eletrooculográficos (EOG) provenientes da aquisição, incluindo janelamento, e aplicação de filtros digitais para processamento e análise. EOG é um sinal que mede e registra o potencial de repouso da retina do olho. Aqui, desenvolvemos um algoritmo para detectar sinais de movimento do globo ocular relativos a eletrodos fixados na face. Os sinais bioelétricos foram coletados de 40 voluntários adultos saudáveis. A metodologia aplicada segue as normas e diretrizes internacionais para aquisição de dados de sinais de ECG e com a anuência do Comitê de Ética em Pesquisa institucional. Dois filtros digitais Savitzky-Golay (SG) e Median Filter (FM), foram comparados. Como resultado, foram desenvolvidos e registrados softwares para janelamento de sinais e comparação entre filtros digitais, sendo o Savitzky-Golay o mais adequado para uso com EOG.

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Fearn, Tom. "Savitzky—Golay Filters". NIR news 11, n.º 6 (diciembre de 2000): 14–15. http://dx.doi.org/10.1255/nirn.593.

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Press, William H. y Saul A. Teukolsky. "Savitzky-Golay Smoothing Filters". Computers in Physics 4, n.º 6 (1990): 669. http://dx.doi.org/10.1063/1.4822961.

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Krishnan, Sunder Ram y Chandra Sekhar Seelamantula. "On the Selection of Optimum Savitzky-Golay Filters". IEEE Transactions on Signal Processing 61, n.º 2 (enero de 2013): 380–91. http://dx.doi.org/10.1109/tsp.2012.2225055.

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Quan, Quan y Kai-Yuan Cai. "Time-domain analysis of the Savitzky–Golay filters". Digital Signal Processing 22, n.º 2 (marzo de 2012): 238–45. http://dx.doi.org/10.1016/j.dsp.2011.11.004.

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Sivagami, A. Vaishali, Ramya Ramakrishnan y A. Subasini. "Weather Prediction Model using Savitzky-Golay and Kalman Filters". Procedia Computer Science 165 (2019): 449–55. http://dx.doi.org/10.1016/j.procs.2020.01.005.

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Niedźwiecki, Maciej y Marcin Ciołek. "Generalized Savitzky–Golay filters for identification of nonstationary systems". Automatica 108 (octubre de 2019): 108477. http://dx.doi.org/10.1016/j.automatica.2019.06.029.

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Schulze, H. Georg, Rod B. Foist, Andre Ivanov y Robin F. B. Turner. "Fully Automated High-Performance Signal-to-Noise Ratio Enhancement Based on an Iterative Three-Point Zero-Order Savitzky—Golay Filter". Applied Spectroscopy 62, n.º 10 (octubre de 2008): 1160–66. http://dx.doi.org/10.1366/000370208786049079.

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The automated processing of data from high-throughput and real-time collection procedures is becoming a pressing problem. Currently the focus is shifting to automated smoothing techniques where, unlike background subtraction techniques, very few methods exist. We have developed a filter based on the widely used and conceptually simple moving average method or zero-order Savitzky–Golay filter and its iterative relative, the Kolmogorov–Zurbenko filter. A crucial difference, however, between these filters and our implementation is that our fully automated smoothing filter requires no parameter specification or parameter optimization. Results are comparable to, or better than, Savitzky–Golay filters with optimized parameters and superior to the automated iterative median filter. Our approach, because it is based on the highly familiar moving average concept, is intuitive, fast, and straightforward to implement and should therefore be of immediate and considerable practical use in a wide variety of spectroscopy applications.

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Nozato, Hideaki, Thomas Bruns, Henrik Volkers y Akihiro Oota. "A study of Savitzky-Golay filters for derivatives in primary shock calibration". ACTA IMEKO 2, n.º 2 (15 de enero de 2014): 41. http://dx.doi.org/10.21014/acta_imeko.v2i2.62.

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This manuscript reports the result of an investigation into two types of digital filters for numerical differentiation of the displacement signal in the case of primary shock calibration of accelerometers. The first is a difference method with a 4th-order Butterworth low-pass (4th BW) filter; the other is a Savitzky-Golay (S-G) filter, which applies a moving polynomial approximation. The computational comparison was applied to low and high amplitude shocks using known excitation functions. Each sum of residuals was compared for the optimized conditions of the 4th BW and S-G filters. The results of computer simulation indicated that the S-G filters exhibited better performance for the derivatives than the 4th BW filters. In addition, an analytical comparison using experimental vibration data also indicated that the S-G filters exhibited better derivative characteristics than the 4th BW filters.

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Candan, Çağatay y Hakan Inan. "A unified framework for derivation and implementation of Savitzky–Golay filters". Signal Processing 104 (noviembre de 2014): 203–11. http://dx.doi.org/10.1016/j.sigpro.2014.04.016.

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Kim, Donghoon, Sungwook Yang y Sangchul Lee. "Rigid Body Inertia Estimation Using Extended Kalman and Savitzky-Golay Filters". Mathematical Problems in Engineering 2016 (2016): 1–7. http://dx.doi.org/10.1155/2016/2962671.

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Inertia properties of rigid body such as ground, aerial, and space vehicles may be changed by several occasions, and this variation of the properties influences the control accuracy of the rigid body. For this reason, accurate inertia properties need to be obtained for precise control. An estimation process is required for both noisy gyro measurements and the time derivative of the gyro measurements. In this paper, an estimation method is proposed for having reliable estimates of inertia properties. First, the Euler equations of motion are reformulated to obtain a regressor matrix. Next, the extended Kalman filter is adopted to reduce the noise effects in gyro angular velocity measurements. Last, the inertia properties are estimated using linear least squares. To achieve reliable and accurate angular accelerations, a Savitzky-Golay filter based on an even number sampled data is utilized. Numerical examples are presented to demonstrate the performance of the proposed algorithm for the case of a space vehicle. The numerical simulation results show that the proposed algorithm provides accurate inertia property estimates in the presence of noisy measurements.

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Miloš, Jiří, Jiří Blumenstein, Aleš Prokeš, Tomáš Mikulášek y Christoph Mecklenbräuker. "Improved RMS Delay Spread Estimation for mmWave Channels Using Savitzky–Golay Filters". Electronics 8, n.º 12 (12 de diciembre de 2019): 1530. http://dx.doi.org/10.3390/electronics8121530.

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In this paper, a novel method for improving the estimation accuracy of the root mean square (RMS) delay spread from the magnitude of the Channel Transfer Function (CTF) is presented. We utilize the level crossing rate metric in the frequency domain, which is based on scalar power measurement. The Savitzky–Golay (S-G) filtering method is used to improve the fidelity of the channel delay spread estimator. The presented concept is simple to implement and inexpensive. The proposed method is tested on the CTF magnitude data measured in the mmWave frequency band at low Signal-to-Noise Ratio (SNR).

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Toonkum, Pollakrit, Nijasri C. Suwanwela y Chedsada Chinrungrueng. "Reconstruction of 3D ultrasound images based on Cyclic Regularized Savitzky–Golay filters". Ultrasonics 51, n.º 2 (febrero de 2011): 136–47. http://dx.doi.org/10.1016/j.ultras.2010.07.003.

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Suwanwela, Nijasri C. "Reconstruction of three-dimensional ultrasound images based on cyclic Savitzky–Golay filters". Journal of Electronic Imaging 20, n.º 1 (1 de enero de 2011): 013026. http://dx.doi.org/10.1117/1.3569121.

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Kennedy, Hugh L. "Improving the frequency response of Savitzky-Golay filters via colored-noise models". Digital Signal Processing 102 (julio de 2020): 102743. http://dx.doi.org/10.1016/j.dsp.2020.102743.

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Niedźwiecki, Maciej Jan, Marcin Ciołek, Artur Gańcza y Piotr Kaczmarek. "Application of regularized Savitzky–Golay filters to identification of time-varying systems". Automatica 133 (noviembre de 2021): 109865. http://dx.doi.org/10.1016/j.automatica.2021.109865.

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González López, Rubén Alberto. "Evaluación de algoritmos para estimar la derivada de presión en pruebas de pozos". Ingeniería y Región 5 (30 de diciembre de 2008): 91–98. http://dx.doi.org/10.25054/22161325.828.

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Aunque hay muchos métodos para hallar la función derivada que brindan buenos resultados en otros escenarios, en ocasiones la naturaleza discreta de las curvas de presión de pozo hacen que el procesamiento de éstas no sea adecuado. Además el ruido que le imprimen a la prueba las herramientas con la que se adquieren los datos y otros fenómenos naturales ajenos al yacimiento, dificulta el análisis y la posterior interpretación de la prueba. Para determinar la función derivada de presión, es bastante común encontrar en la literatura los métodos de Bourdet, Simons y Horne. Últimamente se han utilizado con gran éxito algoritmos polinomiales como el de Spline y otros, no sólo, para hallar la función derivada de presión si no también, para filtrar los datos de la prueba de presión y así poder disminuirlas sobre presiones anormales que muchas veces hacen que éstas no se puedan interpretar. Laexploracióndelosmétodospolinomialeshanpermitidoevaluarloscualitativaycuantitativamente para compararlos con casos teóricos y de campo. Los métodos de mínimos cuadrados móviles y Savitzky – Golay se aplican tanto como filtro y como método derivativo. Así mismo, el método de la familia de los Spline, el Spline Periódico. En todos ellos el arreglo de puntos P vs t se divide en tramos más pequeños ya que ninguna curva de presión se ajusta a una función polinómica. El método de Savitzky – Golay, es muy útil como filtro para reducir el ruido de las pruebas, aunque utilizándolo para hallar la derivada, presentó inconsistencias en la parte del almacenamiento de la prueba, pero para tiempos tardíos resultó ser bastante apropiado. El método de mínimos cuadrados móviles, es recomendable para hallar la función derivada de presión, aunque basta que el polinomio de aproximación sea de grado 3 mientras que la ventana de los datos tratados se recomienda que sea grande. Por último, el método de Spline Periódico no se recomienda para determinar la derivada de pruebas de presión, pues los datos que se obtienen no muestran una tendencia satisfactoria.

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Kawala-Sterniuk, Aleksandra, Michal Podpora, Mariusz Pelc, Monika Blaszczyszyn, Edward Jacek Gorzelanczyk, Radek Martinek y Stepan Ozana. "Comparison of Smoothing Filters in Analysis of EEG Data for the Medical Diagnostics Purposes". Sensors 20, n.º 3 (2 de febrero de 2020): 807. http://dx.doi.org/10.3390/s20030807.

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This paper covers a brief review of both the advantages and disadvantages of the implementation of various smoothing filters in the analysis of electroencephalography (EEG) data for the purpose of potential medical diagnostics. The EEG data are very prone to the occurrence of various internal and external artifacts and signal distortions. In this paper, three types of smoothing filters were compared: smooth filter, median filter and Savitzky–Golay filter. The authors of this paper compared those filters and proved their usefulness, as they made the analyzed data more legible for diagnostic purposes. The obtained results were promising, however, the studies on finding perfect filtering methods are still in progress.

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Sadeghi, Mohammad, Fereidoon Behnia y Rouhollah Amiri. "Window Selection of the Savitzky–Golay Filters for Signal Recovery From Noisy Measurements". IEEE Transactions on Instrumentation and Measurement 69, n.º 8 (agosto de 2020): 5418–27. http://dx.doi.org/10.1109/tim.2020.2966310.

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Elgaud, Mohamed M., Mohd Saiful Dzulkefly Zan, Abdulfatah A. G. Abushagur, Abdulwahhab E. Hamzah, Mohd Hadri Hafiz Mokhtar, Norhana Arsad y Ahmad Ashrif A. Bakar. "Digital Filtering Techniques for Performance Improvement of Golay Coded TDM-FBG Sensor". Sensors 21, n.º 13 (23 de junio de 2021): 4299. http://dx.doi.org/10.3390/s21134299.

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For almost a half-decade, the unique autocorrelation properties of Golay complementary pairs (GCP) have added a significant value to the key performance of conventional time-domain multiplexed fiber Bragg grating sensors (TDM-FBGs). However, the employment of the unipolar form of Golay coded TDM-FBG has suffered from several performance flaws, such as limited improvement of the signal-to-noise ratio (SNIR), noisy backgrounds, and distorted signals. Therefore, we propose and experimentally implement several digital filtering techniques to mitigate such limitations. Moving averages (MA), Savitzky–Golay (SG), and moving median (MM) filters were deployed to process the signals from two low reflectance FBG sensors located after around 16 km of fiber. The first part of the experiment discussed the sole deployment of Golay codes from 4 bits to 256 bits in the TDM-FBG sensor. As a result, the total SNIR of around 8.8 dB was experimentally confirmed for the longest 256-bit code. Furthermore, the individual deployment of MA, MM, and SG filters within the mentioned decoded sequences secured a further significant increase in SNIR of around 4, 3.5, and 3 dB, respectively. Thus, the deployment of the filtering technique alone resulted in at least four times faster measurement time (equivalent to 3 dB SNIR). Overall, the experimental analysis confirmed that MM outperformed the other two techniques in better signal shape, fastest signal transition time, comparable SNIR, and capability to maintain high spatial resolution.

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Stone, David C. "Application of median filtering to noisy data". Canadian Journal of Chemistry 73, n.º 10 (1 de octubre de 1995): 1573–81. http://dx.doi.org/10.1139/v95-195.

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The properties and application of the median filter are investigated using both simulated and real data for signals evolving with time. Comparison is made with existing numerical techniques for drift compensation and noise reduction in analytical measurements such as the moving average and Savitzky–Golay digital filters. The median filter provides a means for dealing with "spiky" noise and separating peaks from a slowly changing baseline, even when the exact nature of the drift and noise distribution is not known. Median filtering is a useful and complementary addition to existing digital filtering techniques, being mathematically robust and readily implemented on any computer platform. Keywords: median filtering, signal noise, signal processing, digital filters, chemometrics, data smoothing.

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Li, Yan, Hua Jun Liu, Guang Lang Bian y Miao Hui Liu. "Aerocraft Real-Time Measured Data Processing Method Based on Combined Filtering". Applied Mechanics and Materials 716-717 (diciembre de 2014): 983–86. http://dx.doi.org/10.4028/www.scientific.net/amm.716-717.983.

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To solve the problems that resulted from using a certain filtering method alone to process the real-time data measured on aerocraft, a new method combined filter and Savitzky-Golay smoothing filter is proposed to process the real-time measuring data, which could classify and segment the measured data of aerocraft trajectory according to its priority and time domain. It could provide useful principle and control procedure of combined filters on different conditions to improve the filter efficiency, and the combined filtering results meet the needs of aerocraft real-time data processing accuracy in different measured sections.

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Arantes Filho, Luis Ricardo, Lamartine Nogueira Frutuoso Guimarães, Francisca Joamila Brito Do Nascimento y Reinaldo Roberto Rosa. "Estratégia de dupla filtragem utilizando o filtro de Savitzky-Golay em dados espectrais de supernovas". Revista Brasileira de Computação Aplicada 11, n.º 2 (26 de junio de 2019): 86–99. http://dx.doi.org/10.5335/rbca.v11i2.9179.

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O desenvolvimento de aplicações que lidam com processamento de sinais deve considerar a qualidade dos dados. Técnicas de aprendizado de máquina e técnicas estatísticas requerem ajustes e normalizações no conjunto de dados antes da análise de um dado fenômeno. Quando um conjunto de dados não é tratado para reduzir inconsistências e ruídos fornecidos por instrumentos ou por condições naturais, a análise acrescenta uma tendência, ou seja, os resultados não podem ser reproduzidos porque o conjunto de dados recebe inconsistências condicionadas pelo ruído. Neste sentido, o trabalho a seguir apresenta um sistema para processamento de sinais e ajuste de dados, utilizando como estudo de caso a aplicação em dados espectrais de supernovas, para configurar uma normalização automática e uniforme em grandes conjuntos de dados. Este trabalho propõe uma estratégia de dupla filtragem utilizando o filtro Savitzky-Golay para otimização da redução de ruído. Este sistema produz um sinal filtrado capaz de garantir a otimização em alguns parâmetros, como o deslocamento mínimo do comprimento de onda comparado ao sinal original, a manutenção da forma do sinal original, a atenuação do ruído no sinal e a qualidade na busca por mínimos e máximos locais. A comparação com outras estratégias da literatura salienta a eficiência do sistema e sua aplicabilidade para diversos tipos de sinais e espectros.

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Cięszczyk, Sławomir. "FREQUENCY RESPONSE OF NORRIS GAP DERIVATIVES AND ITS PROSPERITIES FOR GAS SPECTRA ANALYSIS". Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska 10, n.º 4 (20 de diciembre de 2020): 25–28. http://dx.doi.org/10.35784/iapgos.2101.

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The article deals with an analysis of the properties of Norris gap derivatives. It discusses issues related to determining information from optical spectra measured with spectrometers. Impulse responses of differentiating filters were introduced using both Norris and Savitzky-Golay methods. The amplitude-frequency responses of the first and second order Norris differentiating filters were compared. The length impact of both segment and gaps on the frequency characteristics of filters was compared. The processing of exemplary gas spectra using the discussed technique was subsequently presented. The effect of first and second order derivatives on the spectra of carbon monoxide rotational lines for low resolution measurements is investigated. The Norris method of derivatives are very simple to implement and the calculation of their parameters does not require the use of advanced numerical methods.

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Rzhevskii, Alexander M. y Peter P. Mardilovich. "Generalized Gans—Gill Method for Smoothing and Differentiation of Composite Profiles in Practice". Applied Spectroscopy 48, n.º 1 (enero de 1994): 13–20. http://dx.doi.org/10.1366/0003702944027714.

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A comparison has been made of the effectiveness of smoothing and differentiating Savitzky-Golay filters in terms of the minimization of total error criterion. The advantages of multipassing filters based on quartic/quintic (for smoothing) and cubic/quartic (for differentiation) polynomials have been proved. A generalized method is proposed for the choice of polynomial length, for both smoothing and differentiating filters, in the fine-structure analysis of composite spectra. This method follows the suggestion of P. Gans and G. B. Gill to locate an inflection point on the curve of variance of residuals between observed and smoothed spectra with respect to the polynomial length of the filter applied. A block diagram of the computer program is shown for optimum choice of polynomial lengths, and an example of its application in the analysis of the fine structure of an experimental multiplet band system is demonstrated.

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Huang, Hui, Shiyan Hu y Ye Sun. "A Discrete Curvature Estimation Based Low-Distortion Adaptive Savitzky–Golay Filter for ECG Denoising". Sensors 19, n.º 7 (4 de abril de 2019): 1617. http://dx.doi.org/10.3390/s19071617.

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Electrocardiogram (ECG) sensing is an important application for the diagnosis of cardiovascular diseases. Recently, driven by the emerging technology of wearable electronics, massive wearable ECG sensors are developed, which however brings additional sources of noise contamination on ECG signals from these wearable ECG sensors. In this paper, we propose a new low-distortion adaptive Savitzky-Golay (LDASG) filtering method for ECG denoising based on discrete curvature estimation, which demonstrates better performance than the state of the art of ECG denoising. The standard Savitzky-Golay (SG) filter has a remarkable performance of data smoothing. However, it lacks adaptability to signal variations and thus often induces signal distortion for high-variation signals such as ECG. In our method, the discrete curvature estimation is adapted to represent the signal variation for the purpose of mitigating signal distortion. By adaptively designing the proper SG filter according to the discrete curvature for each data sample, the proposed method still retains the intrinsic advantage of SG filters of excellent data smoothing and further tackles the challenge of denoising high signal variations with low signal distortion. In our experiment, we compared our method with the EMD-wavelet based method and the non-local means (NLM) denoising method in the performance of both noise elimination and signal distortion reduction. Particularly, for the signal distortion reduction, our method decreases in MSE by 33.33% when compared to EMD-wavelet and by 50% when compared to NLM, and decreases in PRD by 18.25% when compared to EMD-wavelet and by 25.24% when compared to NLM. Our method shows high potential and feasibility in wide applications of ECG denoising for both clinical use and consumer electronics.

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Chakraborty, Monisha y Shreya Das. "Determination of Signal to Noise Ratio of Electrocardiograms Filtered by Band Pass and Savitzky-Golay Filters". Procedia Technology 4 (2012): 830–33. http://dx.doi.org/10.1016/j.protcy.2012.05.136.

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Wang, Hejing y Jian Zhou. "Data smoothing and distortion of X-ray diffraction peaks. II. Application". Journal of Applied Crystallography 33, n.º 4 (1 de agosto de 2000): 1136–42. http://dx.doi.org/10.1107/s0021889800006944.

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Based on the analysis of geometric relations, it is found that the amplitude of the distortion of the full width at half-maximum (FWHM) of a peak after smoothing is the largest among the distortions of the seven parameters of a peak: maximum intensity, FWHM, shape, asymmetry, integral intensity, peak position and integral width. Hence the FWHM distortion is used as a criterion of smoothing. The 1% and 5% error limits of smoothing are calculated. Quadratic and quartic polynomial Savitzky–Golay filters are compared. Aberrations of an X-ray diffraction (XRD) peak caused by using double, matched, 1.5 and 0.7 FWHM filters are described in more detail by means of the analyses of internal and external factors. It is found that the smoothing-induced distortions of an actual XRD peak trend towards those of ideal curves. The distortions are classified according to three types of peak. A possible method to obtain the actual peak parameters, called `system smoothing refinement', is presented.

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Alcázar Vargas, Manuel, Javier Pérez Fernández, Juan M. Velasco García, Juan A. Cabrera Carrillo y Juan J. Castillo Aguilar. "A Novel Method for Determining Angular Speed and Acceleration Using Sin-Cos Encoders". Sensors 21, n.º 2 (15 de enero de 2021): 577. http://dx.doi.org/10.3390/s21020577.

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The performance of vehicle safety systems depends very much on the accuracy of the signals coming from vehicle sensors. Among them, the wheel speed is of vital importance. This paper describes a new method to obtain the wheel speed by using Sin-Cos encoders. The methodology is based on the use of the Savitzky–Golay filters to optimally determine the coefficients of the polynomials that best fit the measured signals and their time derivatives. The whole process requires a low computational cost, which makes it suitable for real-time applications. This way it is possible to provide the safety system with an accurate measurement of both the angular speed and acceleration of the wheels. The proposed method has been compared to other conventional approaches. The results obtained in simulations and real tests show the superior performance of the proposed method, particularly for medium and low wheel angular speeds.

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Tomeš, Matěj, Vladimír Weinzettl, Tiago Pereira, Martin Imríšek y Jakub Seidl. "Calculation of edge ion temperature and poloidal rotation velocity from carbon III triplet measurements on the COMPASS tokamak". Nukleonika 61, n.º 4 (1 de diciembre de 2016): 443–51. http://dx.doi.org/10.1515/nuka-2016-0073.

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Abstract A high-resolution spectroscopic system for the measurements of the CIII triplet at 465 nm was installed at the COMPASS tokamak. The Doppler broadening and shift of the measured spectral lines are used to calculate the edge ion temperature and poloidal plasma rotation. At first, the spectroscopic system based on two-grating spectrometer and the calibration procedure is described. The signal processing including detection and removal of spiky features in the signal caused by hard X-rays based on the difference in the behaviour of Savitzky-Golay and median filters is explained. The detection and position estimation of individual spectral lines based on the continuous wavelet transform is shown. The method of fitting of Gaussians using the orthogonal distance regression and estimation of the error of estimation of the rotation velocity and ion temperature is described. At the end, conclusions about the performance of the spectroscopic system and its shortcomings based on summary of results calculated from 2033 processed spectral lines measured in 61 shots are drawn and the possible enhancements are suggested.

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Delwiche, Stephen R. y James B. Reeves. "A Graphical Method to Evaluate Spectral Preprocessing in Multivariate Regression Calibrations: Example with Savitzky—Golay Filters and Partial Least Squares Regression". Applied Spectroscopy 64, n.º 1 (enero de 2010): 73–82. http://dx.doi.org/10.1366/000370210790572007.

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Browarska, Natalia, Aleksandra Kawala-Sterniuk, Jaroslaw Zygarlicki, Michal Podpora, Mariusz Pelc, Radek Martinek y Edward Gorzelańczyk. "Comparison of Smoothing Filters’ Influence on Quality of Data Recorded with the Emotiv EPOC Flex Brain–Computer Interface Headset during Audio Stimulation". Brain Sciences 11, n.º 1 (13 de enero de 2021): 98. http://dx.doi.org/10.3390/brainsci11010098.

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Off-the-shelf, consumer-grade EEG equipment is nowadays becoming the first-choice equipment for many scientists when it comes to recording brain waves for research purposes. On one hand, this is perfectly understandable due to its availability and relatively low cost (especially in comparison to some clinical-level EEG devices), but, on the other hand, quality of the recorded signals is gradually increasing and reaching levels that were offered just a few years ago by much more expensive devices used in medicine for diagnostic purposes. In many cases, a well-designed filter and/or a well-thought signal acquisition method improve the signal quality to the level that it becomes good enough to become subject of further analysis allowing to formulate some valid scientific theories and draw far-fetched conclusions related to human brain operation. In this paper, we propose a smoothing filter based upon the Savitzky–Golay filter for the purpose of EEG signal filtering. Additionally, we provide a summary and comparison of the applied filter to some other approaches to EEG data filtering. All the analyzed signals were acquired from subjects performing visually involving high-concentration tasks with audio stimuli using Emotiv EPOC Flex equipment.

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KIANI, M. A., K. S. SIM, M. E. NIA y C. P. TSO. "Signal-to-noise ratio enhancement on SEM images using a cubic spline interpolation with Savitzky-Golay filters and weighted least squares error". Journal of Microscopy 258, n.º 2 (12 de febrero de 2015): 140–50. http://dx.doi.org/10.1111/jmi.12227.

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Tahir, Sheikh Badar ud din, Ahmad Jalal y Kibum Kim. "Wearable Inertial Sensors for Daily Activity Analysis Based on Adam Optimization and the Maximum Entropy Markov Model". Entropy 22, n.º 5 (20 de mayo de 2020): 579. http://dx.doi.org/10.3390/e22050579.

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Advancements in wearable sensors technologies provide prominent effects in the daily life activities of humans. These wearable sensors are gaining more awareness in healthcare for the elderly to ensure their independent living and to improve their comfort. In this paper, we present a human activity recognition model that acquires signal data from motion node sensors including inertial sensors, i.e., gyroscopes and accelerometers. First, the inertial data is processed via multiple filters such as Savitzky–Golay, median and hampel filters to examine lower/upper cutoff frequency behaviors. Second, it extracts a multifused model for statistical, wavelet and binary features to maximize the occurrence of optimal feature values. Then, adaptive moment estimation (Adam) and AdaDelta are introduced in a feature optimization phase to adopt learning rate patterns. These optimized patterns are further processed by the maximum entropy Markov model (MEMM) for empirical expectation and highest entropy, which measure signal variances for outperformed accuracy results. Our model was experimentally evaluated on University of Southern California Human Activity Dataset (USC-HAD) as a benchmark dataset and on an Intelligent Mediasporting behavior (IMSB), which is a new self-annotated sports dataset. For evaluation, we used the “leave-one-out” cross validation scheme and the results outperformed existing well-known statistical state-of-the-art methods by achieving an improved recognition accuracy of 91.25%, 93.66% and 90.91% when compared with USC-HAD, IMSB, and Mhealth datasets, respectively. The proposed system should be applicable to man–machine interface domains, such as health exercises, robot learning, interactive games and pattern-based surveillance.

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Abdel-Aziz, Omar, Maha F. Abdel-Ghany, Reham Nagi y Laila Abdel-Fattah. "Application of Savitzky–Golay differentiation filters and Fourier functions to simultaneous determination of cefepime and the co-administered drug, levofloxacin, in spiked human plasma". Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 139 (marzo de 2015): 449–55. http://dx.doi.org/10.1016/j.saa.2014.12.046.

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Fedotov, A. A. "Analysis of parameters for smoothing electrocardiographic signals Aleksandr A. Fedotov". Izmeritel`naya Tekhnika, n.º 12 (diciembre de 2019): 47–51. http://dx.doi.org/10.32446/0368-1025it.2019-12-47-51.

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The article is devoted to the consideration of the features of smoothing filtering of ECG signal against the background of electromyographic distortions of various magnitude. The main goal of the research is comparative analysis of various options for the implementation of smoothing filtering of an ECG signal contaminated by myographic interference in order to determine the optimal approach in terms of minimizing biosignal distortions and measurement errors of its amplitude-time characteristics. To obtain quantitative characteristics of effectiveness of various methods for smoothing filtering of the ECG signal, we used an approach based on simulation models of the ECG signal and distortions. A criterion for choosing the optimal parameters for smoothing filtering of the ECG signal based on minimizing the errors in determining the durations of RR-intervals and distortions of the ECG signal was proposed. Various options for smoothing filters are considered: low-pass filtering, multiscale wavelet transform, Savitzky–Golay filtering, moving average filtering. The optimal parameters for each type of filter are determined in terms of minimizing the distortion of the ECG signal and the measurement error of the durations of RR-intervals. The dependences of the change in the measurement error of the durations of RR-intervals on the signal-to-noise ratio, the dependences of the change in the signal distortion coefficient on the signal-to-noise ratio, the plots of processing the noisy fragment of ECG signal by various types of filters are presented. Research have shown that multiscale wavelet transforms of ECG signal with myographic interference is the optimal method for processing an ECG signal, providing minimal measurement errors of RR-intervals with minimal distortion of the ECG signal.

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Vargas Sállago, José Manuel, Irineo Lorenzo López Cruz y Enrique Rico García. "Estimación de la fotosíntesis foliar en jitomate bajo invernadero mediante redes neuronales artificiales". Revista Mexicana de Ciencias Agrícolas 3, n.º 7 (15 de junio de 2018): 1289–304. http://dx.doi.org/10.29312/remexca.v3i7.1334.

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Dentro de la teoría de identificación de sistemas, los modelos de redes neuronales artificiales (ANN) artificial neural networks por sus siglas en inglés, han mostrado gran capacidad para encontrar patrones de relación entre variables de procesos altamente no lineales, así como resolver la limitante de la regresión no lineal, donde no es posible usar variables correlacionadas como entradas. El objetivo de la presente investigación fue modelar la tasa de fotosíntesis foliar de plantas de jitomate, cultivadas bajo invernadero, mediante redes neuronales artificiales, empleando como variables de entrada: temperatura, humedad relativa, déficit de presión de vapor y concentración de dióxido de carbono (CO2) del aire, así como radiación fotosintéticamente activa. El experimento se desarrolló durante 2009 en un invernadero experimental de la Universidad Autónoma de Querétaro, México. Se usó el equipo de fitomonitoreo PTM-48M (Daletown Company, Ltd), para registrar el intercambio de CO2 de las hojas, así como las variables meteorológicas. Para eliminar ruidos de los sensores en las mediciones se aplicó el filtro Savitzky-Golay. Se evaluaron diferentes configuraciones para redes de retropropagación, siendo la de 4 capas con 10 neuronas en la primera capa oculta, 15 en la segunda y 10 más en la tercera, la que generó los mejores índices estadísticos sobre datos de prueba: coeficiente de determinación, R2= 0.9756 y cuadrado medio del error, CME= 0.8532. Tomando las predicciones de la mejor ANN, se realizó una optimización estática, relacionando dos variables climáticas con la tasa de fotosíntesis, mediante gráficas en tercera dimensión, a fin de mostrar estrategias para maximizar la tasa de fotosíntesis.

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Walker, Jessica J. y Christopher E. Soulard. "Phenology Patterns Indicate Recovery Trajectories of Ponderosa Pine Forests After High-Severity Fires". Remote Sensing 11, n.º 23 (26 de noviembre de 2019): 2782. http://dx.doi.org/10.3390/rs11232782.

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Post-fire recovery trajectories in ponderosa pine (Pinus ponderosa Laws.) forests of the southwestern United States are increasingly shifting away from pre-burn vegetation communities. This study investigated whether phenological metrics derived from a multi-decade remotely sensed imagery time-series could differentiate among grass, evergreen shrub, deciduous, or conifer-dominated replacement pathways. We focused on 10 fires that burned ponderosa pine forests in Arizona and New Mexico, USA before the year 2000. A total of 29 sites with discernable post-fire recovery signals were selected within high-severity burn areas. At each site, we used Google Earth Engine to derive time-series of normalized difference vegetation index (NDVI) signals from Landsat Thematic Mapper, Enhanced Thematic Mapper Plus, and Operational Land Imager data from 1984 to 2017. We aggregated values to 8- and 16-day intervals, fit Savitzky–Golay filters to each sequence, and extracted annual phenology metrics of amplitude, base value, peak value, and timing of peak value in the TIMESAT analysis package. Results showed that relative to post-fire conditions, pre-burn ponderosa pine forests exhibit significantly lower mean NDVI amplitude (0.14 vs. 0.21), higher mean base NDVI (0.47 vs. 0.22), higher mean peak NDVI (0.60 vs. 0.43), and later mean peak NDVI (day of year 277 vs. 237). Vegetation succession pathways exhibit distinct phenometric characteristics as early as year 5 (amplitude) and as late as year 20 (timing of peak NDVI). This study confirms the feasibility of leveraging phenology metrics derived from long-term imagery time-series to identify and monitor ecological outcomes. This information may be of benefit to land resource managers who seek indicators of future landscape compositions to inform management strategies.

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Crisóstomo de Castro Filho, Hugo, Osmar Abílio de Carvalho Júnior, Osmar Luiz Ferreira de Carvalho, Pablo Pozzobon de Bem, Rebeca dos Santos de Moura, Anesmar Olino de Albuquerque, Cristiano Rosa Silva, Pedro Henrique Guimarães Ferreira, Renato Fontes Guimarães y Roberto Arnaldo Trancoso Gomes. "Rice Crop Detection Using LSTM, Bi-LSTM, and Machine Learning Models from Sentinel-1 Time Series". Remote Sensing 12, n.º 16 (18 de agosto de 2020): 2655. http://dx.doi.org/10.3390/rs12162655.

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The Synthetic Aperture Radar (SAR) time series allows describing the rice phenological cycle by the backscattering time signature. Therefore, the advent of the Copernicus Sentinel-1 program expands studies of radar data (C-band) for rice monitoring at regional scales, due to the high temporal resolution and free data distribution. Recurrent Neural Network (RNN) model has reached state-of-the-art in the pattern recognition of time-sequenced data, obtaining a significant advantage at crop classification on the remote sensing images. One of the most used approaches in the RNN model is the Long Short-Term Memory (LSTM) model and its improvements, such as Bidirectional LSTM (Bi-LSTM). Bi-LSTM models are more effective as their output depends on the previous and the next segment, in contrast to the unidirectional LSTM models. The present research aims to map rice crops from Sentinel-1 time series (band C) using LSTM and Bi-LSTM models in West Rio Grande do Sul (Brazil). We compared the results with traditional Machine Learning techniques: Support Vector Machines (SVM), Random Forest (RF), k-Nearest Neighbors (k-NN), and Normal Bayes (NB). The developed methodology can be subdivided into the following steps: (a) acquisition of the Sentinel time series over two years; (b) data pre-processing and minimizing noise from 3D spatial-temporal filters and smoothing with Savitzky-Golay filter; (c) time series classification procedures; (d) accuracy analysis and comparison among the methods. The results show high overall accuracy and Kappa (>97% for all methods and metrics). Bi-LSTM was the best model, presenting statistical differences in the McNemar test with a significance of 0.05. However, LSTM and Traditional Machine Learning models also achieved high accuracy values. The study establishes an adequate methodology for mapping the rice crops in West Rio Grande do Sul.

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Podorozhniak, Andrii, Oleksii Balenko y Valentyn Sobol. "MODEL AND ALGORITHMS FOR DETERMINING THE LOCATION AND POSITION OF AGRICULTURAL MACHINERY DURING THE MOVEMENT". Innovative Technologies and Scientific Solutions for Industries, n.º 2 (16) (6 de julio de 2021): 32–38. http://dx.doi.org/10.30837/itssi.2021.16.032.

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The subject of research is the navigation subsystem of autonomous control system to determine the location and position of agricultural machinery during the movement. The purpose of the work is to develop and research model and algorithms to determine the location and position of mobile agricultural machinery using a physical model. The following tasks are solved in the article: development of agricultural machinery physical model to collect information from sensors during movement, further development and research of applicability of algorithms for location and position determination. The following methods are used: methods of mathematical statistics, methods of information systems theory and data processing, methods of random signals filtration. The following results were obtained: during research, the agricultural machinery physical model to collect information from sensors during movement was created. The model includes a GPS receiver, an accelerometer, gyroscope and infrared encoders, to count the rotation of the wheels, as well as its own four wheelbase of agricultural machinery. The modernized GPS coordinate filtration algorithm using a geochex algorithm is proposed, which according to several successively obtained GPS coordinates calculates the hash received coordinates; if the coordinates have the same hash, it can be argued that the vehicle is in the segment of the area that corresponds to this hash. To determine the physical model position during the movement data from the accelerometer and the gyroscope was processed using Savitzky-Golay and Madgwick filters. With the use of wheels’ rotation data, the odometric algorithms for movement and location determining of the agricultural machinery physical model in motion were implemented. Conclusions: to improve the accuracy of estimating the location and position agricultural machinery, algorithms complexation of indicators from different navigation systems should be used to reduce the total error. Research results can be applied in the development of new and modifications of existing navigation subsystems of agricultural machinery autonomous control systems.

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HAZAZ, Mehdi y Toshiyuki MURAKAMI. "Disturbance Observer for DC Motor based on Savitzky-Golay Filters and Application to Bilateral Control". IEEJ Journal of Industry Applications, 2020. http://dx.doi.org/10.1541/ieejjia.19005031.

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Browarska, Natalia, Aleksandra Kawala-Sterniuk y Jarosław Zygarlicki. "Initial study on changes in activity of brain waves during audio stimulation using noninvasive brain–computer interfaces: choosing the appropriate filtering method". Bio-Algorithms and Med-Systems, 29 de octubre de 2020. http://dx.doi.org/10.1515/bams-2020-0051.

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AbstractObjectivesIn this paper series of experiments were carried out in order to check the influence of various sounds on human concentration during visually stimulated tasks performance.MethodsThe obtained data was filtered. For the study purposes various smoothing filters were tested, including Median and Savitzky–Golay Filters; however, median filter only was applied. Implementation of this filter made the obtained data more legible and useful for potential diagnostics purposes. The tests were carried out with the implementation of the Emotiv Flex EEG headset.ResultsThe obtained results were promising and complied with the initial assumptions, which stated that the “relax”-phase, despite relaxing sounds stimuli, is strongly affected with the “focus”-phase with distracting sounds, which is clearly visible in the shape of the recorded EEG data.ConclusionsFurther investigations with broader range of subjects is being currently carried out in order to confirm the already obtained results.

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"Spectrogram Enhanced Pitch Period Tracking using MWSG Filter in Noisy Environments". International Journal of Recent Technology and Engineering 8, n.º 2 (30 de julio de 2019): 5426–28. http://dx.doi.org/10.35940/ijrte.b3542.078219.

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Speech Processing is the study of speech signals which carry individual information such as speaker characteristics, acoustic environment, etc due to which the parameters defining the signal are unique. Pitch Period, Duration, Intensity are the parameters that play the main role in coding speech applications such as authentication, surveillance, speaker recognition. As the conventional filters are static in nature, for non-linear and non-stationary variations of signal parameters adaptive filtering models which are robust are required. Hence the tracking and estimation of the parameters can be done by using Particle-Kalman Filter. It is very important that the signal has to track perfectly even in the presence of noise, by removing the noise and thereby enhancing the output. The approach in this paper is to propose a method for enhancing the performance, using multiple window Savitzky-Golay Filter (MWSG Filter). The performance of filter is measured by parameters Viz., SNR and PSNR

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Rahul, Jagdeep y Marpe Sora. "A novel adaptive window based technique for T wave detection and delineation in the ECG". Bio-Algorithms and Med-Systems 16, n.º 1 (13 de marzo de 2020). http://dx.doi.org/10.1515/bams-2019-0064.

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AbstractThe electrocardiogram (ECG) morphology determines the overall activity of the heart and is the most widely used tool in the diagnostic processes. T wave is a crucial wave component that reveals very useful information regarding various cardiac disorders. In this paper we have proposed a novel T wave detection technique based on adaptive window and simple decision rule. The proposed technique uses two-stage median filters followed by the Savitzky-Golay filter at the pre-processing stage to remove the noises in the ECG signal. The QRS complex is detected for locating the T wave as a reference in one ECG cycle. An R-R interval based window is considered for detecting the T wave, and decision logic depends on the iso-electric line value. The proposed technique is tested on the QT database and self-recorded dataset for its performance evaluation. In the present work, the results achieved for T wave detection sensitivity (Se), positive predictivity (+P), detection error rate (DER), and accuracy (Acc) on the QT database are Se = 97.57%, +P = 99.63%, DER = 2.78%, and Acc = 97.22% with an average time error of (3.468 ± 5.732) ms. The proposed technique shows Se = 99.94%, +P = 99.94%, DER = 0.01%, and Acc = 99.89% on the self-recorded dataset. The proposed technique is also capable of detecting both the upward and downward T wave efficiently in the ECG signal.

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"Dynamic Characteristics of submerged floating tunnel under irregular waves". Journal of Applied and Emerging Sciences, 31 de diciembre de 2019, 121–29. http://dx.doi.org/10.36785/buitems.jaes.303.

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submerged floating tunnel (SFT) is an innovative structural solution for waterway crossings and is based on the idea of Archimedes Buoyancy. The main structure is kept at a certain depth underwater and is placed in position by anchor/mooring cables. SFT becomes a more economical alternative for waterways compared to classical solutions such as cable-supported bridge, immersed tunnel or underground tunnel when the width and depth of the waterway are large enough. As SFT is completely submerged in water and is subjected to extreme environmental conditions such as waves, earthquakes, and hurricanes, therefore, the evaluation the dynamic characteristics of an SFT under irregular waves is a key demand from the design point of view. In this study, the responses of an SFT that is to be built in Qindao Lake of China are investigated under irregular waves. A 3D FEM model for SFT was established, the tunnel was modeled by 3D beam elements and cables were modeled by elastic catenary elements. The irregular waves were modeled by JONSWAP spectrum. The time history analysis was performed under irregular waves and currents. The time-domain simulations were transformed to the frequency domain by Fast Fourier Transform (FFT). The spectra were smoothed using Savitzky-Golay smoothing filters. The transfer functions of SFT horizontal and vertical displacements; and cable tensions were obtained for 30 realizations. Two major peaks have been observed in each transfer function (response spectrum). One of the peaks was associated with the peak wave frequency; the second peak was associated with the translational natural frequency of the SFT.

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