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On principal component analysis of the convex combination of two data matrices and its application to acoustic metamaterial filters

arXiv 2104.07054 ↗First posted 4 Apr 2021math.OC cs.LGcited by 0

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Abstract (arXiv)

In this short paper, a matrix perturbation bound on the eigenvalues found by principal component analysis is investigated, for the case in which the data matrix on which principal component analysis is performed is a convex combination of two data matrices. The application of the theoretical analysis to multi-objective optimization problems (e.g., those arising in the design of acoustic metamaterial filters) is briefly discussed, together with possible extensions.

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  1. 2019Machine-learning techniques for the optimal design of acoustic metamaterialscited by 5

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