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VLSI Architecture for Matrix Inversion using Modified Gram-Schmidt based QR Decomposition
2007
20th International Conference on VLSI Design held jointly with 6th International Conference on Embedded Systems (VLSID'07)
Matrix inversion and triangularization problems are common to a wide variety of communication systems, signal processing applications and solution of a set of linear equations. Matrix inversion is a computationally intensive process and its hardware implementation based on fixed-point (FP) arithmetic is a challenging problem. This paper proposes a fully parallel VLSI architecture under fixed-precision for the inverse computation of a real square matrix using QR decomposition with Modified
doi:10.1109/vlsid.2007.177
dblp:conf/vlsid/SinghPB07
fatcat:r5m3jh4swvawpfg36dpb643wmi