Matrix diagonalization (or termed, matrix eigen-decomposition) is a vital part of matrix theory. Different from static matrix diagonalization problem, in this paper, the more challenging problem, i.e.

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A convolutive frequency-domain backward-model blind source separation (BSS) for directly estimating the unmixing matrix by solving a block-by-block least-squares approximate joint diagonalization (AJD ...

In this tutorial, we will consider the phase diagram of the quantum XXZ Heisenberg model in the presence of a transverse field. Next, we will use dimensionality reduction techniques, namely PCA and ...

Kenneth Merz, Ph.D., of Cleveland Clinic's Center for Computational Life Sciences and a team are exploring how quantum ...

Liang, S. and Pang, H. (1994) Approximate Diagonalization Using the Density Matrix Renormalization-Group Method: A Two-Dimensional-Systems Perspective. Physical Review B, 49, 9214-9217. ... To ...

Caution: Modification indices are not computed if the model matrix is an identity matrix (IDE or ZID), a selection matrix (PER), or the first matrix J in the LINEQS model. If you want to display the ...