A new algorithm for the generalized eigenvalue problem

被引：0
|
作者：
Huper, K
Helmke, U
机构：
来源：
1997 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS I - V: VOL I: PLENARY, EXPERT SUMMARIES, SPECIAL, AUDIO, UNDERWATER ACOUSTICS, VLSI; VOL II: SPEECH PROCESSING; VOL III: SPEECH PROCESSING, DIGITAL SIGNAL PROCESSING; VOL IV: MULTIDIMENSIONAL SIGNAL PROCESSING, NEURAL NETWORKS - VOL V: STATISTICAL SIGNAL AND ARRAY PROCESSING, APPLICATIONS | 1997年
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D O I：
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中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
The problem of finding the generalized eigenvalues and eigenvectors of a pair of real symmetric matrices A and B, with B > 0, can be viewed as a smooth optimization problem on a smooth manifold. We present a cost function approach to the generalized eigenvalue problem which is posed on the product of the n-sphere and Euclidian space R. The critical point set of this cost function is studied. An algorithm is presented based on constrained optimization. A proof of local quadratic convergence is given.
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页码：35 / 38
页数：4
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