Spectral density estimation for linear processes with dependent innovations

Statistics & Probability Letters ◽

10.1016/j.spl.2008.01.019 ◽

2008 ◽

Vol 78 (12) ◽

pp. 1601-1611 ◽

Author(s):

Nadia Bensaïd ◽

Ouafae Yazourh-Benrabah

Keyword(s):

Spectral Density ◽

Density Estimation ◽

Linear Processes ◽

Spectral Density Estimation

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Periodic Splines for Spectral Density Estimation: The Use of Cross Validation for Determining the Degree of Smoothing

Communications in Statistics - Simulation and Computation ◽

10.1080/03610917508548343 ◽

1975 ◽

Vol 4 (2) ◽

pp. 125-141

Author(s):

G. Wahba ◽

S. Wold

Keyword(s):

Spectral Density ◽

Density Estimation ◽

Cross Validation ◽

Spectral Density Estimation

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Robust and Efficient Parametric Spectral Density Estimation for High-Throughput Data

Technometrics ◽

10.1080/00401706.2021.1884134 ◽

2021 ◽

pp. 1-22

Author(s):

Martin Lysy ◽

Feiyu Zhu ◽

Bryan Yates ◽

Aleksander Labuda

Keyword(s):

Spectral Density ◽

Density Estimation ◽

High Throughput ◽

Spectral Density Estimation ◽

High Throughput Data

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Spectral density estimation with amplitude modulation and outlier detection

Annals of the Institute of Statistical Mathematics ◽

10.1007/bf02506479 ◽

2004 ◽

Vol 56 (4) ◽

pp. 611-630 ◽

Author(s):

Jiancheng Jiang ◽

Y. V. Hui

Keyword(s):

Spectral Density ◽

Outlier Detection ◽

Density Estimation ◽

Amplitude Modulation ◽

Spectral Density Estimation

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Input image spectral density estimation for real-time adaption of correlation filters for optical pattern recognition

10.1117/12.262628 ◽

1996 ◽

Author(s):

Anders Grunnet-Jepsen ◽

Sylvie G. Tonda ◽

Vincent Laude

Keyword(s):

Pattern Recognition ◽

Spectral Density ◽

Real Time ◽

Density Estimation ◽

Input Image ◽

Correlation Filters ◽

Spectral Density Estimation ◽

Optical Pattern Recognition ◽

Optical Pattern

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Multi-Channel late reverberation power spectral density estimation based on nuclear norm minimization

2017 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA) ◽

10.1109/waspaa.2017.8170003 ◽

2017 ◽

Author(s):

Ina Kodrasi ◽

Simon Doclo

Keyword(s):

Spectral Density ◽

Density Estimation ◽

Power Spectral Density ◽

Nuclear Norm ◽

Nuclear Norm Minimization ◽

Spectral Density Estimation ◽

Norm Minimization ◽

Power Spectral ◽

Power Spectral Density Estimation

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A reconstruction method for graph signals based on the power spectral density estimation

Digital Signal Processing ◽

10.1016/j.dsp.2021.103347 ◽

2022 ◽

Vol 122 ◽

pp. 103347

Author(s):

Zhihua Yang ◽

Guangrui Yang ◽

Lihua Yang ◽

Qian Zhang

Keyword(s):

Spectral Density ◽

Density Estimation ◽

Power Spectral Density ◽

Reconstruction Method ◽

Spectral Density Estimation ◽

Power Spectral ◽

Power Spectral Density Estimation

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APPLICATION OF WEIGHTING WINDOWS FOR SPECTRAL DENSITY ESTIMATION

10.34220/mamsp_71-77 ◽

2021 ◽

Author(s):

Vera Meerson ◽

O. Khorolsky

Keyword(s):

Fourier Transform ◽

Correlation Function ◽

Spectral Density ◽

Density Estimation ◽

Time Windows ◽

Spectral Density Estimation ◽

The article discusses the application of some of the most important time windows for spectral density estimation determined by the correlogram method (from correlation function) and the periodogram method (from direct fourier transform).

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Wavelets as a regularization technique for spectral density estimation

[1992] Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis ◽

10.1109/tftsa.1992.274231 ◽

2003 ◽

Author(s):

P. Moulin

Keyword(s):

Spectral Density ◽

Density Estimation ◽

Regularization Technique ◽

Spectral Density Estimation

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Closed form frequency domain expressions for best achievable accuracy of spectral density estimation

2004 IEEE International Conference on Acoustics, Speech, and Signal Processing ◽

10.1109/icassp.2004.1326300 ◽

2004 ◽

Author(s):

B. Ninness

Keyword(s):

Spectral Density ◽

Closed Form ◽

Frequency Domain ◽

Density Estimation ◽

Spectral Density Estimation ◽

Achievable Accuracy

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Power Spectral Density Estimation Using Statistical Smoothing of the Linear Difference Model Parameters of the Random Time Series

2019 International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon) ◽

10.1109/fareastcon.2019.8934923 ◽

2019 ◽

Author(s):

V.N. Yakimov ◽

A.V. Mashkov ◽

P.K. Lange ◽

E.E. Yaroslavkina

Keyword(s):

Time Series ◽

Spectral Density ◽

Density Estimation ◽

Power Spectral Density ◽

Random Time ◽

Model Parameters ◽

Difference Model ◽

Spectral Density Estimation ◽

Power Spectral ◽

Power Spectral Density Estimation

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