The determinant of a given square matrix is obtained by iterative matrix order condensation as a product of pivot elements evaluated. As a by-product, it follows that the inverse of this matrix is then evaluated through the extension of the iterative matrix order. Only simple elementary arithmetical operations without any high mathematical process are involved in the fast and straightforward basic iterative method. Remarkably, without failing the inverse of any square matrix, the revised optimal iterative method would compute within minutes, whether real or complex, singular or non-singular, and interestingly enough even for size as big as 999×999. If the calculation of small size inverse matrices is feasible, the manually extended iteration procedure is often generated to shorten the iteration steps.
Author (s) Details
Feng Cheng Chang
Allwave Corporation, Torrance, California, USA.
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