Skip to main content
SpringerLink
Log in
SpringerLink
Log in

Signal Detection in Non-Gaussian Noise

  • Textbook
  • © 1988

Overview

Authors:
  1. Saleem A. Kassam

    1. Department of Electrical Engineering, University of Pennsylvania, Philadelphia, USA

    View author publications

    You can also search for this author in PubMed   Google Scholar

Part of the book series: Springer Texts in Electrical Engineering (STELE)

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (7 chapters)

  1. Front Matter

    Pages i-ix
    Download chapter PDF

  2. Elements of Statistical Hypothesis Testing

    • Saleem A. Kassam
    Pages 1-23

  3. Detection of Known Signals in Additive Noise

    • Saleem A. Kassam
    Pages 24-70

  4. Some Univariate Noise Probability Density Function Models

    • Saleem A. Kassam
    Pages 72-96

  5. Optimun Data Quantization in Known-Signal Detection

    • Saleem A. Kassam
    Pages 97-126

  6. Detection of known Narrowband Signals in Narrowband Noise

    • Saleem A. Kassam
    Pages 127-150

  7. Detection of Narrowband Signals with Random Phase Angles

    • Saleem A. Kassam
    Pages 151-184

  8. Detection of Random Signals in Additive Noise

    • Saleem A. Kassam
    Pages 185-214

  9. Back Matter

    Pages 215-234
    Download chapter PDF
Back to top

Keywords

About this book

This book contains a unified treatment of a class of problems of signal detection theory. This is the detection of signals in addi­ tive noise which is not required to have Gaussian probability den­ sity functions in its statistical description. For the most part the material developed here can be classified as belonging to the gen­ eral body of results of parametric theory. Thus the probability density functions of the observations are assumed to be known, at least to within a finite number of unknown parameters in a known functional form. Of course the focus is on noise which is not Gaussian; results for Gaussian noise in the problems treated here become special cases. The contents also form a bridge between the classical results of signal detection in Gaussian noise and those of nonparametric and robust signal detection, which are not con­ sidered in this book. Three canonical problems of signal detection in additive noise are covered here. These allow between them formulation of a range of specific detection problems arising in applications such as radar and sonar, binary signaling, and pattern recognition and classification. The simplest to state and perhaps the most widely studied of all is the problem of detecting a completely known deterministic signal in noise. Also considered here is the detection random non-deterministic signal in noise. Both of these situa­ of a tions may arise for observation processes of the low-pass type and also for processes of the band-pass type.

Authors and Affiliations

  • Department of Electrical Engineering, University of Pennsylvania, Philadelphia, USA

    Saleem A. Kassam

Bibliographic Information

  • Book Title: Signal Detection in Non-Gaussian Noise

  • Authors: Saleem A. Kassam

  • Series Title: Springer Texts in Electrical Engineering

  • DOI: https://doi.org/10.1007/978-1-4612-3834-8

  • Publisher: Springer New York, NY

  • eBook Packages: Springer Book Archive

  • Copyright Information: Dowden & Culver, Inc. 1988

  • Softcover ISBN: 978-1-4612-8370-6Published: 17 September 2011

  • eBook ISBN: 978-1-4612-3834-8Published: 06 December 2012

  • Series ISSN: 1431-8482

  • Edition Number: 1

  • Number of Pages: IX, 234

  • Topics: Communications Engineering, Networks

Publish with us

Policies and ethics

Back to top

Search

Navigation