Abstract:
This thesis describes the implementation and evaluation of an adaptive time-domain algorithm
for signal enhancement from multiple-sensor observations. The algorithm is first
derived as a noncausal time-domain algorithm, then converted into a causal, recursive form.
A more computationally efficient gradient-based parameter estimation step is also presented.
The results of several experiments using synthetic data are shown. These experiments first
illustrate that the algorithm works on data meeting all the assumptions made by the algorithm,
then provide a basis for comparing the performance of the algorithm against the
performance of a noncausal frequency-domain algorithm solving the same problem. Finally,
an evaluation is made of the performance of the simpler gradient-based parameter
estimation step.
