Relevant bibliographies by topics / Autocorrelation matrix

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Autocorrelation matrix'

Author: Grafiati
Published: 3 June 2025
Last updated: 19 July 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Autocorrelation matrix.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Autocorrelation matrix"

1

Conrey, J. B., D. W. Farmer, J. P. Keating, M. O. Rubinstein, and N. C. Snaith. "Autocorrelation of Random Matrix Polynomials." Communications in Mathematical Physics 237, no. 3 (2003): 365–95. http://dx.doi.org/10.1007/s00220-003-0852-2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Sun, Shuai, and Haiping Zhang. "Flow-Data-Based Global Spatial Autocorrelation Measurements for Evaluating Spatial Interactions." ISPRS International Journal of Geo-Information 12, no. 10 (2023): 396. http://dx.doi.org/10.3390/ijgi12100396.

Full text
Abstract:
Spatial autocorrelation analysis is essential for understanding the distribution patterns of spatial flow data. Existing methods focus mainly on the origins and destinations of flow units and the relationships between them. These methods measure the autocorrelation of gravity or the positional and directional autocorrelations of flow units that are treated as objects. However, the intrinsic complexity of actual flow data necessitates the consideration of not only gravity, positional, and directional autocorrelations but also the autocorrelations of the variables of interest. This study propose
APA, Harvard, Vancouver, ISO, and other styles
3

Chachlakis, Dimitris G., and Panos P. Markopoulos. "Structured autocorrelation matrix estimation for coprime arrays." Signal Processing 183 (June 2021): 107987. http://dx.doi.org/10.1016/j.sigpro.2021.107987.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Andrews, Donald W. K. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation." Econometrica 59, no. 3 (1991): 817. http://dx.doi.org/10.2307/2938229.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

JIAO, Chuan-hai, Ke-ren WANG, and Shuo MEN. "Cooperative blind spectrum sensing using autocorrelation matrix." Journal of China Universities of Posts and Telecommunications 18, no. 3 (2011): 47–53. http://dx.doi.org/10.1016/s1005-8885(10)60062-3.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Podstrigaev, Alexey, and Nhan Nguen Chong. "STUDYING THE ACCURACY OF DETERMINING THE LOCATION OF RADIO EMISSION SOURCES WITH COMPLEX SIGNALS WHEN USING A MATRIX RECEIVER WITH AN AUTOCORRELATION ALGORITHM AT THE OUTPUT." Automation and modeling in design and management 2022, no. 2 (2022): 4–12. http://dx.doi.org/10.30987/2658-6436-2022-2-4-12.

Full text
Abstract:
The root-mean-square errors of the position lines are estimated when using direction-finding and difference-range methods based on a matrix receiver with an autocorrelation algorithm at the output. The study compares the accuracy of determining the location of radio emission sources with linear-frequency-modulated and phase-code-shifted signals by a matrix receiver with an autocorrelation algorithm at the output and a matrix receiver with a detector algorithm at the output. A comparative analysis of calculating the ratio between the root-mean-square errors of locating radio emission sources is
APA, Harvard, Vancouver, ISO, and other styles
7

West, Kenneth D. "Another heteroskedasticity- and autocorrelation-consistent covariance matrix estimator." Journal of Econometrics 76, no. 1-2 (1997): 171–91. http://dx.doi.org/10.1016/0304-4076(95)01788-7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Khalili, Malika, Robert Leconte, and François Brissette. "Stochastic Multisite Generation of Daily Precipitation Data Using Spatial Autocorrelation." Journal of Hydrometeorology 8, no. 3 (2007): 396–412. http://dx.doi.org/10.1175/jhm588.1.

Full text
Abstract:
Abstract There are a number of stochastic models that simulate weather data required for various water resources applications in hydrology, agriculture, ecosystem, and climate change studies. However, many of them ignore the dependence between station locations exhibited by the observed meteorological time series. This paper proposes a multisite generation approach of daily precipitation data based on the concept of spatial autocorrelation. This theory refers to spatial dependence between observations with respect to their geographical adjacency. In hydrometeorology, spatial autocorrelation ca
APA, Harvard, Vancouver, ISO, and other styles
9

Cao, Hai-Yan, and Zhen-Yu Ye. "Theoretical analysis and algorithm design of optimized pilot for downlink channel estimation in massive MIMO systems based on compressed sensing." Acta Physica Sinica 71, no. 5 (2022): 050101. http://dx.doi.org/10.7498/aps.71.20211504.

Full text
Abstract:
Aiming at the pilot design problem in channel estimation of large-scale multiple input multiple output (MIMO) systems, an adaptive autocorrelation matrix reduction parameter pilot optimization algorithm based on channel reconstruction error rate minimization is proposed under the framework of compression perception theory. Firstly, the system model and orthogonal matching pursuit (OMP) algorithm are introduced. Secondly, for minimizing the channel reconstruction error rate, the relation between the expected value of the correlation decision in each iteration of the OMP algorithm and the recons
APA, Harvard, Vancouver, ISO, and other styles
10

Laikova, L. G., T. A. Tereshchenko, and Y. S. Yamnenko. "Matrix calculation of correlation characteristics based on spectral methods." Технология и конструирование в электронной аппаратуре, no. 3-4 (2020): 11–16. http://dx.doi.org/10.15222/tkea2020.3-4.11.

Full text
Abstract:
The paper is devoted to the problem of calculation of autocorrelation function that is important for solving the tasks that require finding the repeating intervals of the signal or defining the main frequency of the signal against the background of non-stationary noise. The authors propose an algorithm to transform the connection between arithmetic and logical correlation functions in oriented basis into the matrix form. Comparative analysis is conducted for the computational complexity of different types of autocorrelation functions using different spectral methods — Fourier, Walsh, and orien
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Autocorrelation matrix"

1

Kalender, Emre. "Parametric Estimation Of Clutter Autocorrelation Matrix For Ground Moving Target Indication." Master's thesis, METU, 2013. http://etd.lib.metu.edu.tr/upload/12615313/index.pdf.

Full text
Abstract:
In airborne radar systems with Ground Moving Target Indication (GMTI) mode, it is desired to detect the presence of targets in the interference consisting of noise, ground clutter, and jamming signals. These interference components usually mask the target return signal, such that the detection requires suppression of the interference signals. Space-time adaptive processing is a widely used interference suppression technique which uses temporal and spatial information to eliminate the effects of clutter and jamming and enables the detection of moving targets with small radial velocity. However,
APA, Harvard, Vancouver, ISO, and other styles
2

Hu, Qilin. "Autocorrelation-based factor analysis and nonlinear shrinkage estimation of large integrated covariance matrix." Thesis, London School of Economics and Political Science (University of London), 2016. http://etheses.lse.ac.uk/3551/.

Full text
Abstract:
The first part of my thesis deals with the factor modeling for high-dimensional time series based on a dimension-reduction viewpoint. we allow the dimension of time series N to be as large as, or even larger than the sample size of the time series. The estimation of the factor loading matrix and subsequently the factors are done via an eigenanalysis on a non-negative definite matrix constructed from autocorrelation matrix. The method is dubbed as AFA. We give explicit comparison of the convergence rates between AFA with PCA. We show that AFA possesses the advantage over PCA when dealing with s
APA, Harvard, Vancouver, ISO, and other styles
3

Zeileis, Achim. "Econometric computing with HC and HAC covariance matrix estimators." Institut für Statistik und Mathematik, WU Vienna University of Economics and Business, 2004. http://epub.wu.ac.at/520/1/document.pdf.

Full text
Abstract:
Data described by econometric models typically contains autocorrelation and/or heteroskedasticity of unknown form and for inference in such models it is essential to use covariance matrix estimators that can consistently estimate the covariance of the model parameters. Hence, suitable heteroskedasticity-consistent (HC) and heteroskedasticity and autocorrelation consistent (HAC) estimators have been receiving attention in the econometric literature over the last 20 years. To apply these estimators in practice, an implementation is needed that preferably translates the conceptual properties of t
APA, Harvard, Vancouver, ISO, and other styles
4

Chun, Yongwan. "Behavioral specifications of network autocorrelation in migration modeling an analysis of migration flows by spatial filtering /." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1187188476.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

REBUFELLO, ENRICO. "Developing new paradigms for quantum measurements." Doctoral thesis, Politecnico di Torino, 2021. http://hdl.handle.net/11583/2875749.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Hirukawa, Masayuki. "Heteroskedasticity and autocorrelation consistent covariance matrix estimation." 2004. http://www.library.wisc.edu/databases/connect/dissertations.html.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Weng, Hong-Yuan, and 翁宏源. "Using Covariance matrix and Autocorrelation Invariance for 2D-object Recognition." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/5dhd2w.

Full text
Abstract:
碩士<br>國立臺北科技大學<br>工業工程與管理系所<br>93<br>This study proposes an effective recognition system of two-dimensional objects by incorporating the eigenvalues of covariance matrix with invariance of autocorrelation coefficient. The proposed method first uses mean threshold method to derive the image. Then, a morphologic operation is adopted to extract the boundary of a digital object. Two-stage feature extract is designed in this study. First, the boundary of object is represented by calculating the eigenvalues of the covariance matrix according to the region of support. Secondly, the sampled eigenvalue
APA, Harvard, Vancouver, ISO, and other styles

Books on the topic "Autocorrelation matrix"

1

Estrella, Arturo. Consistent covariance matrix estimation in probit models with autocorrelated errors. Federal Reserve Bank of New York, 1998.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
2

Passos, Jose. Finite-sample performance of the heteroskedasticity and autocorrelation consistence covariance matrix estimators. University of Bristol, Department of Economics, 1994.

Find full text
APA, Harvard, Vancouver, ISO, and other styles

Book chapters on the topic "Autocorrelation matrix"

1

Gong, Yanzhu, Bing Zhu, Hui Wang, and Yutian Wang. "Beat Analysis Based on Autocorrelation Phase Matrix." In Lecture Notes in Electrical Engineering. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34528-9_19.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Shen, Min, and Lin Zhu. "Microphone Array Autocorrelation Matrix and Error Analysis." In Lecture Notes in Electrical Engineering. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27323-0_74.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Pisetta, Vincent, and Djamel A. Zighed. "Similarity and Kernel Matrix Evaluation Based on Spatial Autocorrelation Analysis." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04125-9_45.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Arbia, Giuseppe. "Problems in the Estimation of the Spatial Autocorrelation Function Arising From the Form of the Weights Matrix." In Transformations Through Space and Time. Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-009-4430-5_15.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Likhachev, Vladimir P., Alexey S. Podstrigaev, Nguyen Trong Nhan, Vadim V. Davydov, and Nikita S. Myazin. "Study of the Accuracy of Determining the Location of Radio Emission Sources with Complex Signals When Using Autocorrelation and Matrix Receivers in Broadband Tools for Analyzing the Electronic Environment." In Lecture Notes in Computer Science. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-65726-0_29.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Griffith, Daniel A., and Larry J. Layne. "Popular Spatial Autoregressive And Geostatistical Models." In A Casebook For Spatial Statistical Data Analysis. Oxford University PressNew York, NY, 1999. http://dx.doi.org/10.1093/oso/9780195109580.003.0003.

Full text
Abstract:
Abstract Parallels between spatial autoregression and geostatistics are outlined in §1.2. To recapitulate, discussions of spatial series tend to focus on either spatial autocorrelation (geostatistics) or partial spatial autocorrelation (spatial autoregression). Although these two subfields have been evolving autonomously and in parallel, they are closely linked. Recalling Figure 1.1, both spatial statistics and geostatistics fall under the heading of multivariate analysis. The former frequently is concerned with aggregations of phenomena into discrete regions, while the latter principally is concerned with more or less continuously occurring attributes. By exploiting latent spatial autocorrelation in georeferenced data, spatial autoregression usually seeks to enhance statistical description and increase statistical precision, whereas geostatistics often seeks to generate spatial predictions. The prediction focus of the latter provides a link between these two subdisciplines through the missing data problem. The exact algebraic correspondence established with this spatial prediction/missing data linkage emphasizes that spatial autoregression directly deals with the inverse-variance covariance matrix while geostatistics directly deals with the variance-covariance matrix itself(§1.1).
APA, Harvard, Vancouver, ISO, and other styles
7

Nakagawa, Masahiro. "A Chaos Auto-Associative Model with Chebyshev Activation Function." In Chaos Theory - Recent Advances, New Perspectives and Applications [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.106147.

Full text
Abstract:
In this work, we shall put forward a novel chaos memory retrieval model with a Chebyshev-type activation function as an artificial chaos neuron. According to certain numerical analyses of the present association model with autocorrelation connection matrix between neurons, the dependence of memory retrieval properties on the initial Hamming distance between the input pattern and a target pattern to be retrieved among the embedded patterns will be presented to examine the retrieval abilities, i.e. the memory capacity of the associative memory.
APA, Harvard, Vancouver, ISO, and other styles
8

Griffith, Daniel A., and Larry J. Layne. "Analysis Of Georeferenced Socioeconomic Attribute Variables." In A Casebook For Spatial Statistical Data Analysis. Oxford University PressNew York, NY, 1999. http://dx.doi.org/10.1093/oso/9780195109580.003.0004.

Full text
Abstract:
Abstract Georeferenced socioeconomic data sets are commonly used for example calculations in popular standard statistics books, such as Neter et al. (1996, pp.1367-69), Venables and Ripley (1994, 67, 74, 81, 127, 320), and Johnson and Wichern (1992, 392,393, 604-7, 624,626). Unfortunately, as Anselin and Griffith (1988) and Anselin and Hudak (1992) note, authors of this class of texts either gloss over (e.g., Johnson and Wichern 1992, 392) or acknowledge and then dismiss the importance of (e.g., Neter et al.1996, l 048) latent spatial dependencies. Notable exceptions are furnished by Bailey and Gatrell (1995, 249) and by Sen and Srivastava (1990), who not only recognize the presence and importance of spatial autocorrelation in georeferenced data, but also include two Chicago examples (pp. 94, 152) involving socioeconomic attribute variables, as well as a geographic connectivity matrix (p. 153). In practice, spatial effects latent in socioeconomic data increasingly are playing an explicitly important role in the everyday life of people.
APA, Harvard, Vancouver, ISO, and other styles
9

Ross, John, Igor Schreiber, and Marcel O. Vlad. "Experimental Test and Applications of Correlation Metric Construction." In Determination of Complex Reaction Mechanisms. Oxford University Press, 2006. http://dx.doi.org/10.1093/oso/9780195178685.003.0010.

Full text
Abstract:
In this chapter we present an experimental test case of the deduction of a reaction pathway and mechanism by means of correlation metric construction from time-series measurements of the concentrations of chemical species. We choose as the system an enzymatic reaction network, the initial steps of glycolysis. Glycolysis is central in intermediary metabolism and has a high degree of regulation. The reaction pathway has been well studied and thus it is a good test for the theory. Further, the reaction mechanism of this part of glycolysis has been modeled extensively. The quantity and precision of the measurements reported here are sufficient to determine the matrix of correlation functions and, from this, a reaction pathway that is qualitatively consistent with the reaction mechanism established previously. The existence of unmeasured species did not compromise the analysis. The quantity and precision of the data were not excessive, and thus we expect the method to be generally applicable. This CMC experiment was carried out in a continuous-flow stirred-tank reactor (CSTR). The reaction network considered consists of eight enzymes, which catalyze the conversion of glucose into dihydroxyacetone phosphate and glyceraldehyde phosphate. The enzymes were confined to the reactor by an ultrafiltration membrane at the top of the reactor. The membrane was permeable to all low molecular weight species. The inputs are (1) a reaction buffer, which provides starting material for the reaction network to process, maintains pH and pMg, and contains any other species that act as constant constraints on the system dynamics, and (2) a set of “control species” (at least one), whose input concentrations are changed randomly every sampling period over the course of the experiment. The sampling period is chosen such that the system almost, but not quite, relaxes to a chosen nonequilibrium steady state. The system is kept near enough to its steady state to minimize trending (caused by the relaxation) in the time series, but far enough from the steady state that the time-lagged autocorrelation functions for each species decay to zero over three to five sampling periods. This long decay is necessary if temporal ordering in the network is to be analyzed.
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Autocorrelation matrix"

1

Zhang, Chi, Xi Zhang, Genwang Liu, et al. "Ship detection from PolSAR imagery using the hybrid polarimetric autocorrelation matrix." In Third International Conference on Geographic Information and Remote Sensing Technology (GIRST 2024), edited by Francesco Benedetto, Fabio Tosti, and Roman Alvarez. SPIE, 2025. https://doi.org/10.1117/12.3059711.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Maruyama, Kohei, Ikumasa Yoshida, and Hidehiko Sekiya. "Fundamental study on the influence of vehicle speed on BWIM considering autocorrelation in bridge dynamic response." In IABSE Symposium, Tokyo 2025: Environmentally Friendly Technologies and Structures: Focusing on Sustainable Approaches. International Association for Bridge and Structural Engineering (IABSE), 2025. https://doi.org/10.2749/tokyo.2025.1684.

Full text
Abstract:
&lt;p&gt;The Bridge Weigh-in-Motion (BWIM) system estimates axle weights and gross vehicle weights (GVW) but is affected by modeling errors due to dynamic responses from traffic loads. Conventional BWIM assumes white noise for residuals, which overlooks dynamic response characteristics. To improve estimation accuracy, previous studies consider the autocorrelation of dynamic responses using the covariance matrix of residuals. This matrix may be affected by driving conditions, including vehicle speed. This study investigates the potential effect of driving conditions, particularly vehicle speed,
APA, Harvard, Vancouver, ISO, and other styles
3

Eck, Douglas. "Beat Tracking using an Autocorrelation Phase Matrix." In 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing. IEEE, 2007. http://dx.doi.org/10.1109/icassp.2007.367319.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Wu, Feifan, Xiaolong Li, Jingtian Wang, and Yao Zhao. "Image Upsampling Detection Based on Autocorrelation Matrix." In 2024 9th International Conference on Cloud Computing and Big Data Analytics (ICCCBDA). IEEE, 2024. http://dx.doi.org/10.1109/icccbda61447.2024.10569570.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Senturk, Zekeriya, Omer Emre Yetgin, and Ozgul Salor. "Voiced-unvoiced classification of speech using autocorrelation matrix." In 2014 22nd Signal Processing and Communications Applications Conference (SIU). IEEE, 2014. http://dx.doi.org/10.1109/siu.2014.6830601.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Ipanov, Roman N., and Aleksey A. Komarov. "Coding Matrix of Polyphase Probing Signal with Zero Autocorrelation Zone." In 2023 25th International Conference on Digital Signal Processing and its Applications (DSPA). IEEE, 2023. http://dx.doi.org/10.1109/dspa57594.2023.10113455.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Bäckström, Tom, and Christian R. Helmrich. "Decorrelated innovative codebooks for ACELP using factorization of autocorrelation matrix." In Interspeech 2014. ISCA, 2014. http://dx.doi.org/10.21437/interspeech.2014-586.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Khojasteh, Mohammad J., Morteza H. Shoreh, and Jawad A. Salehi. "Circulant matrix representation of PN-sequences with ideal autocorrelation property." In 2015 Iran Workshop on Communication and Information Theory (IWCIT). IEEE, 2015. http://dx.doi.org/10.1109/iwcit.2015.7140218.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Zhu, Jiang, and Yunyi Yan. "Scale adaptive correlation filter tracking based on the autocorrelation matrix." In CIOP100, edited by Yue Yang. SPIE, 2018. http://dx.doi.org/10.1117/12.2504572.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Xiaoxia Cai, Xiaobo Chen, Hong Chen, and Ji Liu. "Step combination cooperative spectrum sensing algorithm based on autocorrelation matrix." In 2011 Global Mobile Congress (GMC). IEEE, 2011. http://dx.doi.org/10.1109/gmc.2011.6103924.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Autocorrelation matrix"

1

West, Kenneth. Another Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator. National Bureau of Economic Research, 1995. http://dx.doi.org/10.3386/t0183.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Autocorrelation matrix' for particular source types:
Journal articles
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography