Computational Methods for Real-time Adaptive Multichannel Signal ProcessingCornell University, 1995 - 172 pages |
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Page 51
... QR algorithm applied to R " R. Corollary : Refinement - Only FST and TQR - SVD produce the same sequences of ... algorithm during each update . Dowling et . al . [ 9 ] have already shown that a TQR - step applied to an upper triangular ...
... QR algorithm applied to R " R. Corollary : Refinement - Only FST and TQR - SVD produce the same sequences of ... algorithm during each update . Dowling et . al . [ 9 ] have already shown that a TQR - step applied to an upper triangular ...
Page 83
... QR algorithm applied to the sample covariance matrix is equivalent to an interation of two QR factorizations ( called a " transpose QR iteration " ) applied to the data matrix . In this appendix we will show that , in terms of subspaces ...
... QR algorithm applied to the sample covariance matrix is equivalent to an interation of two QR factorizations ( called a " transpose QR iteration " ) applied to the data matrix . In this appendix we will show that , in terms of subspaces ...
Page 88
... algorithm are equivalent to an iteration of the symmetric QR algorithm . Thus , the FST refinement step is also equivalent to the symmetric QR algorithm ( in terms of separating the two subspaces ) . Step 5 : In this final step , the off ...
... algorithm are equivalent to an iteration of the symmetric QR algorithm . Thus , the FST refinement step is also equivalent to the symmetric QR algorithm ( in terms of separating the two subspaces ) . Step 5 : In this final step , the off ...
Contents
Introduction | 7 |
Subspace Tracking Mapped onto Parallel Architectures | 9 |
Review of Multisensor Processing and Parallel Mapping | 16 |
Copyright | |
3 other sections not shown
Common terms and phrases
adaptive sensor array bearing estimation Cell Definition column comm comm complexity Computers & Applications Concurrent Computers condition estimator Conference on Hypercube convergence correlation matrix cost functions Dependence Graph DOA estimate dominant subspace double precision eigenvalues execution flops Graph for Stage hardware Householder transformation hypercube Hypercube Concurrent Computers IEEE Transactions Intel iPSC/860 Intel Paragon iWarp linear least squares linear speedup Mapping algorithms Minimax multiprocessors node processor noise subspace Number of Processors O(Nr operations optimization orthonormal parallel parameters performance plane rotations power domain Principal Angles QR factorization Rank Adaptive FST rank increase rank revealing real-time recursive least squares refinement step require resulting RO-FST sensor array processing shown in Figure signal eigenstructure signal flow graph Signal Processing signal subspace simulated annealing singular value decomposition singular values snapshot Speech and Signal subgraph subspace tracking algorithms tasks techniques TQR-SVD Transactions on Acoustics uniform linear array update vector wavefront