2021
DOI: 10.1002/nla.2420
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A Rayleigh quotientā€gradient neural network method for computing š’µā€eigenpairs of general tensors

Abstract: Recently, Zhao, Zheng, Liang and Xu (A locally and cubically convergent algorithm for computing š’µā€eigenpairs of symmetric tensors. Numer Linear Algebra Appl, 2020, 27:e2284) studied on an efficient method for computing š’µā€eigenpairs of symmetric tensors. Whereas, symmetric tensors are just special tensors. This article is concerned with the computation of š’µā€eigenpairs of general real tensors. We propose a Rayleigh quotientā€gradient neural network model (RGNN) for computing š’µā€eigenpairs of a general real ten… Show more

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Cited by 5 publications
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