On the derivation of parallel filter structures for adaptive eigenvalue and singular value decompositions

A graphical derivation is presented for a parallel filter structure (systolic array) for updating eigenvalue and singular value decompositions. The derivation of this array is non-trivial due to the presence of feedback loops and data contra-flow in the underlying signal flow graph (SFG). This would...

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Bibliographic Details
Published in1995 International Conference on Acoustics, Speech, and Signal Processing Vol. 5; pp. 3247 - 3250 vol.5
Main Authors Moonen, M., Deprettere, E., Proudler, I.K., McWhirter, J.G.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1995
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Summary:A graphical derivation is presented for a parallel filter structure (systolic array) for updating eigenvalue and singular value decompositions. The derivation of this array is non-trivial due to the presence of feedback loops and data contra-flow in the underlying signal flow graph (SFG). This would normally prohibit pipelined processing. However, it is shown that suitable delays may be introduced to the SFG by performing simple algorithmic transformations which compensate for the interference of crossing data flows and eliminate the critical feedback loops. The pipelined array is then obtained either by 2-slowing and retiming the SFG or by means of dependence graph scheduling and assignment, and turns out to be an improved version of the array presented in Moonen et al. (1993).
ISBN:0780324315
9780780324312
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.1995.479577