By Topic

IEEE Signal Processing Magazine

Issue 6 • Nov 1996

Filter Results

Displaying Results 1 - 4 of 4
  • Genetic algorithms and their applications

    Publication Year: 1996, Page(s):22 - 37
    Cited by:  Papers (195)  |  Patents (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (4936 KB)

    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 adapt... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • The genetic search approach. A new learning algorithm for adaptive IIR filtering

    Publication Year: 1996, Page(s):38 - 46
    Cited by:  Papers (49)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2816 KB)

    An “evolutionary” approach called the genetic algorithm (GA) was introduced for multimodal optimization in adaptive IIR filtering. However, the disadvantages of using such an algorithm are slow convergence and high computational complexity. Initiated by the merits and shortcomings of the gradient-based algorithms and the evolutionary algorithms, we developed a new hybrid search methodo... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • The expectation-maximization algorithm

    Publication Year: 1996, Page(s):47 - 60
    Cited by:  Papers (520)  |  Patents (13)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2872 KB)

    A common task in signal processing is the estimation of the parameters of a probability distribution function. Perhaps the most frequently encountered estimation problem is the estimation of the mean of a signal in noise. In many parameter estimation problems the situation is more complicated because direct access to the data necessary to estimate the parameters is impossible, or some of the data ... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Blind image deconvolution revisited

    Publication Year: 1996, Page(s):61 - 63
    Cited by:  Papers (76)  |  Patents (11)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1160 KB)

    The article discusses the major approaches, such as projection based blind deconvolution and maximum likelihood restoration, we overlooked previously (see ibid., no.5, 1996). We discuss them for completeness along with some other works found in the literature. As the area of blind image restoration is a rapidly growing field of research, new methods are constantly being developed View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.

Aims & Scope

IEEE Signal Processing Magazine publishes tutorial-style articles on signal processing research and applications, as well as columns and forums on issues of interest. Its coverage ranges from fundamental principles to practical implementation, reflecting the multidimensional facets of interests and concerns of the community. Its mission is to bring up-to-date, emerging and active technical developments, issues, and events to the research, educational, and professional communities. It is also the main Society communication platform addressing important issues concerning all members.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Min Wu
University of Maryland, College Park
United States 

http://www/ece.umd.edu/~minwu/