Multiple processor architectures for real time parameter estimation

Several multiple processor architectures which allow parallel implementations of the recursive least-squares estimation algorithm are presented and evaluated. The multiple processor architectures are based on the transputer which supports the process model of computation and allows the distribution of concurrent processes on different processors. The computational complexity of the estimation algorithm for a nr*m matrix of parameters can be reduced from O(nr*m/sup 2/) to O(m) using suitable systolic architectures. Also shown are computation time measurements. The parallel architectures allow an effective implementation of the estimation algorithm, even in complex applications which require a computation time of hundreds of microseconds.<
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