This article introduces the genetic algorithm (GA) as an emerging optimization algorithm for signal processing. After a discussion of traditional optimization techniques, it reviews the fundamental operations of a simple GA and discusses procedures to improve its functionality. The properties of the GA that relate to signal processing are summarized, and a number of applications, such as IIR adaptive filtering, time delay estimation, active noise control, and speech processing, that are being successfully implemented are described.
Weighted Median (WM) filters have the robustness and edge preserving capability of the classical median filter and resemble linear FIR filters in certain properties. Furthermore...
This paper investigates some properties of the separable filter resulting from successive applications of a one-dimensional median filter on the rows and columns of an image. Al...
A detailed analysis of a particular adaptive filter has been carried out and the required extension of the theory to the general case is indicated. The filter measures the spect...
In a previous report (Ghitza, 1987, [1]) we described a computational model based upon the temporal characteristics of the information in the auditory nerve fiber firing pattern...
The authors present an efficient architecture to synthesize filters of arbitrary orientations from linear combinations of basis filters, allowing one to adaptively steer a filte...
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