Conjugate Gradient Method For Orthogonal Matrix Optimization Using Cayley Transform

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概要

• 論文の詳細を見る

• Matrix optimization problems required by several applications in signal and image processing appear with orthogonality constraints. It has been shown that the natural gradient performs better than the conventional gradient in orthogonal matrix optimization using the Cayley transform. However, to develop practical orthogonal matrix optimization. it is desirable to apply faster algorithms such as the variable metric method and the conjugate gradient method. The present study applies those methods to orthogonal matrix optimization with the Cayley transform and proposes to replace the conventional gradient terms appeared in the update rules of those methods by the natural gradient. A numerical simulation using joint diagonalization problem shows that the replacement considerably improves the performance of those methods.

• 一般社団法人電子情報通信学会の論文
• 2013-08-22

著者

• Hori Gen

  Faculty of Business Administration, Asia University

• HORI Gen

  Faculty of Business Administration, Asia University:Brain Science Institute, RIKEN

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• Conjugate Gradient Method For Orthogonal Matrix Optimization Using Cayley Transform

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