Theory and Computation of Complex Tensors and its Applications

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<div><div>The book provides an introduction of very recent results about the tensors and mainly focuses on the authors' work and perspective. A systematic description about how to extend the numerical linear algebra to the numerical multi-linear algebra is also delivered in this book. The authors design the neural network model for the computation of the rank-one approximation of real tensors, a normalization algorithm to convert some nonnegative tensors to plane stochastic tensors and a probabilistic algorithm for locating a positive diagonal in a nonnegative tensors,&nbsp;adaptive randomized algorithms for computing the approximate tensor decompositions, and&nbsp;the QR type method for computing U-eigenpairs of complex tensors.</div><div><br></div><div>This book could be used for the Graduate course, such as Introduction to Tensor. Researchers may also find it helpful as a reference in tensor research.</div></div>