Efficient VLSI architectures for matrix factorizations

The SVD (Singular Value Decomposition) is a critical matrix factorization in many real-time computations from an application domain which includes signal processing and robotics; and complex data matrices are encountered in engineering practice. This thesis advocates the use of CORDIC (Coordinate Rotation Digital Computer) arithmetic for parallel computation of the SVD/eigenvalue decomposition of arbitrary complex/Hermitian matrices using Jacobi-like algorithms on processor arrays.;The algorithms and architectures derive from extending the theory of Jacobi-like matrix factorizations to multi-step and inexact pivot (2 x 2) sub-matrix diagonalizations. Based on the former approach of multi-step diagonalization, and using a two-sided 2 x 2 unitary transformation amenable to CORDIC termed ;All proposed algorithms are cast in...