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Methodologies in spectral analysis of large dimensional random matrices, a review

by Z. D. Bai - STATIST. SINICA , 1999
"... In this paper, we give a brief review of the theory of spectral analysis of large dimensional random matrices. Most of the existing work in the literature has been stated for real matrices but the corresponding results for the complex case are also of interest, especially for researchers in Electri ..."
Abstract - Cited by 454 (39 self) - Add to MetaCart
In this paper, we give a brief review of the theory of spectral analysis of large dimensional random matrices. Most of the existing work in the literature has been stated for real matrices but the corresponding results for the complex case are also of interest, especially for researchers

On Spectral Clustering: Analysis and an algorithm

by Andrew Y. Ng, Michael I. Jordan, Yair Weiss - ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS , 2001
"... Despite many empirical successes of spectral clustering methods -- algorithms that cluster points using eigenvectors of matrices derived from the distances between the points -- there are several unresolved issues. First, there is a wide variety of algorithms that use the eigenvectors in slightly ..."
Abstract - Cited by 1713 (13 self) - Add to MetaCart
Despite many empirical successes of spectral clustering methods -- algorithms that cluster points using eigenvectors of matrices derived from the distances between the points -- there are several unresolved issues. First, there is a wide variety of algorithms that use the eigenvectors

Consistency of spectral clustering

by Ulrike von Luxburg, Mikhail Belkin, Olivier Bousquet , 2004
"... Consistency is a key property of statistical algorithms, when the data is drawn from some underlying probability distribution. Surprisingly, despite decades of work, little is known about consistency of most clustering algorithms. In this paper we investigate consistency of a popular family of spe ..."
Abstract - Cited by 572 (15 self) - Add to MetaCart
under strong additional assumptions, which, as we demonstrate, are not always satisfied in real data. We conclude that our analysis provides strong evidence for the superiority of normalized spectral clustering in practical applications. We believe that methods used in our analysis will provide a basis

Spectral analysis of data

by Yossi Azar, Amos Fiat, Anna R. Karlin, Frank Mcsherry, Jared Saia - In Proc. of 33rd STOC
"... ..."
Abstract - Cited by 168 (7 self) - Add to MetaCart
Abstract not found

SPECTRAL ANALYSIS OF ORIENTED FEATURES IN

by unknown authors , 2015
"... KIMMO KARTASALO: Spectral analysis of oriented features in micrographs ..."
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KIMMO KARTASALO: Spectral analysis of oriented features in micrographs

Laplacian eigenmaps and spectral techniques for embedding and clustering.

by Mikhail Belkin , Partha Niyogi - Proceeding of Neural Information Processing Systems, , 2001
"... Abstract Drawing on the correspondence between the graph Laplacian, the Laplace-Beltrami op erator on a manifold , and the connections to the heat equation , we propose a geometrically motivated algorithm for constructing a representation for data sampled from a low dimensional manifold embedded in ..."
Abstract - Cited by 668 (7 self) - Add to MetaCart
map that is defined on the entire manifold. The framework of analysis

Spectral Analysis of Internet Topologies

by Christos Gkantsidis, Milena Mihail, Ellen Zegura , 2003
"... We perform spectral analysis of the Internet topology at the AS level, by adapting the standard spectral filtering method of examining the eigenvectors corresponding to the largest eigenvalues of matrices related to the adjacency matrix of the topology. We observe that the method suggests clusters o ..."
Abstract - Cited by 86 (6 self) - Add to MetaCart
We perform spectral analysis of the Internet topology at the AS level, by adapting the standard spectral filtering method of examining the eigenvectors corresponding to the largest eigenvalues of matrices related to the adjacency matrix of the topology. We observe that the method suggests clusters

Spectral Analysis for Neural Signals

by Bijan Pesaran Phd
"... This chapter introduces concepts fundamental to spectral analysis and applies spectral analysis to char-acterize neural signals. Spectral analysis is a form of time series analysis and concerns a series of events ..."
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This chapter introduces concepts fundamental to spectral analysis and applies spectral analysis to char-acterize neural signals. Spectral analysis is a form of time series analysis and concerns a series of events

Electrophysiology—Spectral Analysis of Arrhythmias

by Juan Jose ́ Sánchez-muñoz, Jose ́ Luis Rojo-álvarez , 2008
"... Spectral analysis of intracardiac electrograms during induced and spontaneous ventricular fibrillation in humans ..."
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Spectral analysis of intracardiac electrograms during induced and spontaneous ventricular fibrillation in humans

Spectral analysis

by Xiao-ma Gu, You-ji Ding, Zhi Luo, Brigitte Schmieder , 1981
"... Abstract. We present the analysis of Hα spectra obtained during a two-ribbon flare observed on the solar disk on May 16, 1981 at Yunnan Observatory with the Spectra-Spectroheliograph (SSHG). The complicated asymmetric profiles produced by the post-flare loops overlying flare ribbons are analysed wit ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
Abstract. We present the analysis of Hα spectra obtained during a two-ribbon flare observed on the solar disk on May 16, 1981 at Yunnan Observatory with the Spectra-Spectroheliograph (SSHG). The complicated asymmetric profiles produced by the post-flare loops overlying flare ribbons are analysed
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