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By exploiting the inherent parallelism in digital signal processing algorithms, significant savings in area and power consumption may be achieved. Completely parallel computation can lead to excessive area, thus mapping the algorithm onto reduced computational resources becomes beneficial. As a drawback, data interconnections become more complex and require storage in order to maintain computationally...
Both the matrix inversion and solving a set of linear equations can be computed with the aid of the Cholesky decomposition. In this paper, the Cholesky decomposition is mapped to the typical resources of digital signal processors (DSP) and our implementation applies a novel way of computing the fixed-point inverse square root function. The presented principles result in savings in the number of clock...
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