کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
563557 | 1451939 | 2016 | 9 صفحه PDF | دانلود رایگان |
• Two Jacobi-like algorithms are established under a reasonable assumption.
• The GERALD2b algorithm converges the fastest among the four algorithms.
• Convergence statistics are shown to illustrate the performances of algorithms.
In this paper, two new algorithms are proposed for non-orthogonal joint matrix diagonalization under Hermitian congruence. The idea of these two algorithms is based on the so-called Jacobi algorithm for solving the eigenvalues problem of Hermitian matrix. The algorithms are then called ‘general Jabobi-like diagonalization’ algorithms (GERALD). They are based on the search of two complex parameters by the minimization of a quadratic criterion corresponding to a measure of diagonality. Lastly, numerical simulations are conducted to illustrate the effective performances of the GERALD algorithms.
Journal: Signal Processing - Volume 128, November 2016, Pages 440–448