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Adaptive Constrained DCT-LMS Time Delay Estimation AlgorithmJian, Jiun-Je 27 June 2000 (has links)
n the problem of time delay estimation (TDE), the desired source signals of interest are
correlated and with a specific spectral distribution. In such cases, the convergence speed using
the conventional approaches, viz., time domain adaptive constrained and unconstrained LMS
TDE algorithms, becomes slowly and the performance of TDE will be degraded, dramatically.
In fact, the convergence rate depends highly on the distribution of spectral density of the
desired signal sources. Also, the performance of TDE is affected by the background noises,
accordingly.
To circumvent the problem described above, in this thesis, a transformed domain adaptive
constrained filtering scheme, refers to the constrained adaptive DCT-LMS algorithm, for TDE
is devised. We show that this new proposed constrained algorithm, with the so-called direct
delay estimation formula, for non-integer TDE does perform better than the conventional time
domain adaptive constrained and unconstrained LMS TDE algorithms and the unconstrained
adaptive DCT-LMS TDE algorithm.
Finally, to further reduce the spread of eigenvalue in the unconstrained adaptive
DCT-LMS algorithm, the Gram-Schmidt orthogonalizer approach realizing by the adaptive
Escalator is investigated. It indicates that bias of TDE will occur without using the constraint
of weight vector. That is, it could not be used to alleviate the effect due to background noises.
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