Adaptive diagonalization for canonical correlation analysis

Mohammed A. Hasan

doi:10.1109/IJCNN.2007.4371249

Adaptive diagonalization for canonical correlation analysis

Mohammed A. Hasan

Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Canonical correlation analysis is an essential technique in many fields such as multivariate statistical analysis and signal processing. In this paper, un-constrained optimization criteria for extracting the actual canonical correlation coordinates are proposed. The resulting gradient dynamical system is thoroughly analyzed in terms of stability and the limiting behavior of the system as t → ∞. One of the main features of this approach is that orthogonal basis for canonical variates which diagonalizes the coherence matrix is automatically obtained. A numerical example is included to demonstrate the performance of the proposed algorithm.

Original language	English (US)
Title of host publication	The 2007 International Joint Conference on Neural Networks, IJCNN 2007 Conference Proceedings
Pages	1906-1911
Number of pages	6
DOIs	https://doi.org/10.1109/IJCNN.2007.4371249
State	Published - 2007
Event	2007 International Joint Conference on Neural Networks, IJCNN 2007 - Orlando, FL, United States Duration: Aug 12 2007 → Aug 17 2007

Publication series

Name	IEEE International Conference on Neural Networks - Conference Proceedings
ISSN (Print)	1098-7576

Other

Other	2007 International Joint Conference on Neural Networks, IJCNN 2007
Country/Territory	United States
City	Orlando, FL
Period	8/12/07 → 8/17/07

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Hasan, MA 2007, Adaptive diagonalization for canonical correlation analysis. in The 2007 International Joint Conference on Neural Networks, IJCNN 2007 Conference Proceedings., 4371249, IEEE International Conference on Neural Networks - Conference Proceedings, pp. 1906-1911, 2007 International Joint Conference on Neural Networks, IJCNN 2007, Orlando, FL, United States, 8/12/07. https://doi.org/10.1109/IJCNN.2007.4371249

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AB - Canonical correlation analysis is an essential technique in many fields such as multivariate statistical analysis and signal processing. In this paper, un-constrained optimization criteria for extracting the actual canonical correlation coordinates are proposed. The resulting gradient dynamical system is thoroughly analyzed in terms of stability and the limiting behavior of the system as t → ∞. One of the main features of this approach is that orthogonal basis for canonical variates which diagonalizes the coherence matrix is automatically obtained. A numerical example is included to demonstrate the performance of the proposed algorithm.

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Adaptive diagonalization for canonical correlation analysis

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