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Statistical analysis of an eigendecomposition based method for 2-D frequency estimation

Hua Yang, Yingbo Hua
1994 Automatica  
An eigendecomposition based method for twodimensional frequency estimation is analyzed in this paper.  ...  In this paper, a number of fundamental relations inherent in the MP method are revealed which lead to a general expression of the large-sample covariances of the estimated twodimensional frequencies.  ...  Acknowledgment--The authors would like to thank the reviewers for their valuable comments.  ... 
doi:10.1016/0005-1098(94)90235-6 fatcat:vjmgefugbferzkftdcfywbecs4

Adaptive Randomized Dimension Reduction on Massive Data [article]

Gregory Darnell and Stoyan Georgiev and Sayan Mukherjee and Barbara E Engelhardt
2015 arXiv   pre-print
The scalability of statistical estimators is of increasing importance in modern applications.  ...  In this paper we develop an approach for dimension reduction that exploits the assumption of low rank structure in high dimensional data to gain both computational and statistical advantages.  ...  Figure 2 : 2 Rank estimation of ARSVD. Figure 3 : 3 CPU time for three matrix decomposition methods with respect to number of features.  ... 
arXiv:1504.03183v1 fatcat:yz6lrheik5ccpgn5kldx4dhqdy

Effective gene prediction by high resolution frequency estimator based on least-norm solution technique

Manidipa Roy, Soma Barman
2014 EURASIP Journal on Bioinformatics and Systems Biology  
One of the most important spectrum analysis techniques based on the concept of subspace is the least-norm method.  ...  results show that the proposed method has better as well as an effective approach towards gene prediction.  ...  Spectral analysis by eigendecomposition In this article, eigendecomposition of the autocorrelation matrix has been motivated as an approach for frequency estimation of DNA sequence.  ... 
doi:10.1186/1687-4153-2014-2 pmid:24386895 pmcid:PMC3895782 fatcat:qm4tpgwthjbp3a4be4472nomji

Computationally Efficient Subspace-Based Method for Direction-of-Arrival Estimation Without Eigendecomposition

J. Xin, A. Sano
2004 IEEE Transactions on Signal Processing  
In this paper, we propose a new computationally efficient subspace-based method without eigendecomposition (SUMWE) for the direction-of-arrival (DOA) estimation of narrowband signals impinging on a uniform  ...  Further an adaptive implementation of the SUMWE is presented for tracking the time-varying directions of slowly moving (relative to the sampling rate) signals.  ...  For alleviating the difficulty of subspace-based methods, some computationally simple subspace-based direction estimation methods without eigendecomposition have been developed [4] - [7] .  ... 
doi:10.1109/tsp.2004.823469 fatcat:obug4e2zcre4jegcqufsbhdxou

Data-driven Estimation of Sinusoid Frequencies [article]

Gautier Izacard, Sreyas Mohan, Carlos Fernandez-Granda
2021 arXiv   pre-print
This yields a fast, fully-automatic method for frequency estimation that achieves state-of-the-art results.  ...  The goal is to estimate the frequency of each component in a multisinusoidal signal from a finite number of noisy samples.  ...  The method is shown to be competitive with the periodogram and eigendecomposition-based methods for a range of noise levels, but requires an estimate of the number of sinusoidal components as an input.  ... 
arXiv:1906.00823v3 fatcat:sy6fgytqgjcdrnyd2o3kiloije

Research on DOA Estimation of Multi-Component LFM Signals Based on the FRFT

Haitao QU, Rihua WANG, Wu QU, Peng ZHAO
2009 Wireless Sensor Network  
A novel algorithm for the direction of arrival (DOA) estimation based on the fractional Fourier transform (FRFT) is proposed.  ...  In a word, a demodulated DOA estimation algorithm is proposed and is applied to 1-D and 2-D angle estimation by dint of ULA and UCA respectively.  ...  Due to the above analysis, we propose a novel DOA estimation algorithm based on FRFT using UCA, as for the multi-component LFM signals, using the characteristics of time-frequency rotation and demodulation  ... 
doi:10.4236/wsn.2009.13023 fatcat:sl6trg67ovaoro4kblxzejgdba

Time Series Forecasting Using Independent Component Analysis

Theodor D. Popescu
2009 Zenodo  
The paper gives also a review of the main algorithms for independent component analysis in the case of instantaneous mixture models, using second and high-order statistics.  ...  The paper presents a method for multivariate time series forecasting using Independent Component Analysis (ICA), as a preprocessing tool.  ...  By Assumption 6, an estimate of R y can be clasically constructed from the eigendecomposition of an estimate of R x .  ... 
doi:10.5281/zenodo.1074779 fatcat:x2fv4zgetrc25n3zv7okbjequu

Stator current analysis by subspace methods for fault detection in induction machines

Youness Trachi, Elhoussin Elbouchikhi, Vincent Choqueuse, Mohamed Benbouzid
2015 IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society  
The main objective of this paper is to identify fault signatures at an early stage by using high-resolution frequency estimation techniques.  ...  In particular, we present two subspace methods, which are Root-MUSIC and ESPRIT. Once the frequencies are determined, the amplitude estimation is obtained by using the Least Squares Estimator (LSE).  ...  Their expressions for the four considered fault types are given by f o = N b 2 f r 1 − D b Dc cos β f i = N b 2 f r 1 + D b Dc cos β f b = Dc D b f r 1 − D 2 b D 2 c cos 2 β f ca = 1 2 f r 1 − D b Dc cos  ... 
doi:10.1109/iecon.2015.7392639 dblp:conf/iecon/TrachiECB15 fatcat:aihct6gfy5ecfdty2wras7x3ma

The EAR Project

Julien Bonnal, Sylvain Argentieri, Patrick Danès, Jérome Manhès, Philippe Souères, Marc Renaud
2010 Journal of the Robotics Society of Japan  
Ongoing work concerns (i) a thorough statistical evaluation of the sensor, (ii) the hardcoding of beamforming through an "overlap-andsave" fast convolution technique, (iii) the hardcoding of MUSIC based  ...  So, the array interspace d is defined as the Shannon spatial sampling period d = λ 3[kHz] /2 = 5.66 [cm] .  ...  His interests are modeling and control of mobile manipulators and robot audition.  ... 
doi:10.7210/jrsj.28.10 fatcat:n2gbmkucn5h4rkuqvd3pgk6osi

A matrix-pencil approach to blind separation of colored nonstationary signals

Chunqi Chang, Zhi Ding, Sze Fong Yau, F.H.Y. Chan
2000 IEEE Transactions on Signal Processing  
For many signal sources such as speech with distinct, nonwhite power spectral densities, second-order statistics of the received signal mixture can be exploited for signal separation.  ...  Based on the matrix pencil, an ESPRIT-type algorithm is derived to get an optimal solution in least square sense.  ...  Second-order statistics-based methods do not require the non-Gaussian assumption. They may generate better performance than algorithms based on higher order statistics for short data length.  ... 
doi:10.1109/78.824690 fatcat:z4us3473xze7jknom4h2uwxz4e

Monte Carlo Singular Spectrum Analysis (SSA) Revisited: Detecting Oscillator Clusters in Multivariate Datasets

Andreas Groth, Michael Ghil
2015 Journal of Climate  
The results of this analysis provide further evidence for shared mechanisms of variability between the Gulf Stream and the North Atlantic Oscillation in the interannual frequency band.  ...  The reliability of the proposed methodology is examined in an idealized setting for a cluster of harmonic oscillators immersed in red noise.  ...  Robertson for helpful suggestions.  ... 
doi:10.1175/jcli-d-15-0100.1 fatcat:lqvddop7xnghbccxvpemrskhp4

JOINT DOD AND DOA ESTIMATION FOR BISTATIC MIMO RADAR WITHOUT EIGENVALUE DECOMPOSITION

Hao Chen, Lu Gan, Zhaohui Wu, Xiaoming Liu, Jinji Ma
2018 Progress In Electromagnetics Research Letters  
A low computational complexity direction of departure (DOD) and direction of arrival (DOA) estimation method is derived for bistatic multiple-input multiple-output (MIMO) radar.  ...  Simulation results verify that the proposed method holds better performance than the unitary estimation of signal parameters via rotational invariance technique and joint diagonalization direction matrix  ...  In [11] , an angle estimation method based on Capon is proposed, which needs to search in two-dimensional (2-D) .  ... 
doi:10.2528/pierl18100106 fatcat:d2slk2qhmjahzouptlgbghto4e

Mesoscopic-scale functional networks in the primate amygdala [article]

Jeremiah K Morrow, Michael X Cohen, Katalin M Gothard
2020 biorxiv/medrxiv   pre-print
A generalized eigendecomposition-based method of source separation isolated coactivity patterns, or components, that in neurophysiological terms correspond to putative subnetworks.  ...  We have extracted from local field potentials recorded simultaneously from multiple locations within the primate amygdala (Macaca mulatta) spatially defined and statistically separable responses to visual  ...  Additional information Author contributions Ethics Animal experimentation: All procedures comply with the NIH guidelines for the use of non-human primates in research as outlined in the Guide for the  ... 
doi:10.1101/2020.02.24.963587 fatcat:kkophbkidffpvodkz6jjbhz2zq

Computationally Efficient Subspace-Based Method for Angle Estimation without Eigendecomposition in Bistatic MIMO Radar

Baobao Liu, Junying Zhang, Cong Xu
2016 ICIC Express Letters  
In this paper, we propose a new computationally simple subspace-based method for joint estimation of direction of departure (DOD) and direction of arrival (DOA), combining multistage Wiener filter (MSWF  ...  Due to no need of eigendecomposition operation, theoretical analysis indicates that the proposed algorithm has lower complexity compared with the unitary ESPRIT and ESPRIT algorithms.  ...  Fundamental Research Funds for the Central Universities of China (Nos.  ... 
doi:10.24507/icicel.10.12.2861 fatcat:qgqebrmah5fnzhj5wwdwzb4wgu

On subspace based sinusoidal frequency estimation

M. Kristensson, M. Jansson, B. Ottersten
1999 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258)  
Subspace based methods for frequency estimation rely on a lowrank system model that is obtained by collecting the observed scalar valued data samples into vectors.  ...  Also, a statistically attractive Markov-like procedure [1] for this class of methods has been proposed in the literature. Herein, the Markov estimator is re-investigated.  ...  In this paper, the statistical properties of subspace based estimators applied to windowed data models are examined using a subspace based sinusoidal frequency estimator as an example.  ... 
doi:10.1109/icassp.1999.756285 dblp:conf/icassp/KristenssonJO99 fatcat:my3kellgdnbefeieffuk6b5yju
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