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SVD and Signal Processing, III
book

SVD and Signal Processing, III

by M. Moonen, B. De Moor
March 1995
Intermediate to advanced content levelIntermediate to advanced
498 pages
23h 58m
English
Elsevier Science
Content preview from SVD and Signal Processing, III
300
S. Hosur et al.
If the input vector xn is transformed to un = ETxn, where E is the unitary eigenvector
matrix of ttx, then the output process zn would be de-correlated. However, this implies
that we need to perform an eigen decomposition of the autocorrelation matrix or a singular
value decomposition of the data matrix at every adaptation, implying a computational
computational complexity of O(N 3) for every adaptation. One could replace E with V,
where V is any unitary matrix which block diagonalizes Rx, separating the signal subspaces
from the noise subspace, but this still takes O(N ...
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Publisher Resources

ISBN: 9780444821072