OPTIMAL VLSI NETWORKS FOR MULTIDIMENSIONAL TRANSFORMS
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abstract
This short note presents a new class of AT2optimal networks for computing the multidimensional Discrete Fourier Transform. Although optimal networks have been proposed previously, the networks proposed in this short note are based on a new methodology for mapping large A-shuffle networks, K 2, onto smaller area networks that maintain the optimality of the DFT network. Such networks are used to perform the index-rotation operations needed by the multidimensional computation. The resulting networks have simple regular layouts, and can be easily partitioned among several chips in order to reduce the number of inputoutput pins per chip. 1994 IEEE