Parallel VLSI computing array implementation for signal subspace updating algorithm

The parallel VLSI computing array implementation is discussed for novel signal subspace iteration algorithm (SSIA) proposed by I. Karasalo (1986). By making use of a sparse structure, a linearly connected VLSI computing structure is developed for the singular valve decomposition operation used in this algorithm. It is first shown that by making use of a sparse structure matrix the computing time of this algorithm for a single processor can be reduced from O(N³) to O(N²), where N is the dimensional of the signal subspace. Then it is shown that the parallel architecture can reduce the overall computing time for single-valued decomposition from O(N²) to O(N)using O(N) processors. This reduces the total computing time of SSIA from max (O(K ²), O(N²K)) with a single processor to O(K) with O(N ²) processors, where K is the dimension of the covariance matrix