Statistical and adaptive signal processing pdf
Adaptive filter - WikipediaAn adaptive filter is a system with a linear filter that has a transfer function controlled by variable parameters and a means to adjust those parameters according to an optimization algorithm. Because of the complexity of the optimization algorithms, almost all adaptive filters are digital filters. Adaptive filters are required for some applications because some parameters of the desired processing operation for instance, the locations of reflective surfaces in a reverberant space are not known in advance or are changing. The closed loop adaptive filter uses feedback in the form of an error signal to refine its transfer function. Generally speaking, the closed loop adaptive process involves the use of a cost function , which is a criterion for optimum performance of the filter, to feed an algorithm, which determines how to modify filter transfer function to minimize the cost on the next iteration. The most common cost function is the mean square of the error signal.
Fundamentals of Signal Processing - Statistical and Adaptive Signal Processing-03
Sundeep Prabhakar Chepuri
Adaptive Filtering pp Cite as. This chapter includes a brief review of deterministic and random signal representations. Due to the extent of those subjects our review is limited to the concepts that are directly relevant to adaptive filtering. The properties of the correlation matrix of the input signal vector are investigated in some detail, since they play a key role in the statistical analysis of the adaptive filtering algorithms. Unable to display preview.
Wideband spectrum sensing techniques for wireless sensors. Chepuri and G. Sparse sensing for statistical inference. Foundations and Trends in Signal Processing , Vol. Segarra, S. Chepuri, A.