Consideration is given to the development of a highly parallel, block-type, order-recursive algorithm for least-squares finite-impulse-response (LS FIR) filter identification and prediction. The computation of the required reflection coefficients is achieved by a technique that does not involve inner vector product operations. Its origin can be traced to the classical Schur algorithm for Toeplitz systems. The algorithm derived is simple and can be implemented on a linear array of O(p) modular processing elements with localized communication requirements, where p is the order of the system, which makes it suitable for VLSI implementation. In a parallel processing environment, the algorithm can be completed in O(p)+O(L) time units, where L is the length of the data block. A novel mode of operation that computes the reflection coefficients as well as the unknown filter's impulse response concurrently and on the same linear processor array is proposed. The algorithm is suitable either for processing a single block of data or for a block adaptive mode of operation, and it can track variations from block to block. The use of the algorithm for parameter adaptation on each time instant is discussed. >
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