Abstract
The design of efficient parallel processing implementations for speeding up the computationally intensive estimation of higher order statistics (HOS) has been recognized as an important task by the signal processing community. We report on the synthesis of minimum running time (latency) data-parallel algorithms that can be employed to compute all moment lags, up to the 3rd or 4th-order, on the MasPar-1 single instruction multiple data (SIMD) parallel system. By construction the synthesized SIMD algorithms require constant memory per processing element (PE), thus allowing the processing of 1-D input data sequences with as many as M=2/sup 10/ data samples. Simulation results are presented showing the gain in speedup and execution times, as compared to optimized versions of the serial estimation algorithm running in powerful workstations.
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