Signal Detection Theory

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Signal Detection Theory

Author: Vi͡acheslav Petrovich Tuzlukov
language: en
Publisher: Springer Science & Business Media
Release Date: 2001
This new text/reference is a comprehensive presentation of fundamental problems for the generalized approach to signal detection theory. New approaches and methods are discussed, as well as experimental results with physical systems. An essential resource for professionals and researchers in electrical engineering and working with modern signal detection problems in radar, communications, wireless communications, acoustics, remote sensing, and geophysical signal processing. The problem of noise immunity is a key problem for complex signal processing systems research in science and engineering. New approaches and problems of such complexity study allows the development of a better quality of signal detection in noise. This book is devoted to a new generalized approach to signal detection theory. The main purpose is to present the basic fundamental concepts of the generalized approach to signal processing in noise and to show how it may be applied in various areas of signal processing. The generalized approach allows extension of the well-known boundaries of the potential noise immunity set up by classical and modern signal detection theories. New approaches for construction of detec
Detection Theory

Author: Neil A. Macmillan
language: en
Publisher: Psychology Press
Release Date: 2004-09-22
Detection Theory is an introduction to one of the most important tools for analysis of data where choices must be made and performance is not perfect. Originally developed for evaluation of electronic detection, detection theory was adopted by psychologists as a way to understand sensory decision making, then embraced by students of human memory. It has since been utilized in areas as diverse as animal behavior and X-ray diagnosis. This book covers the basic principles of detection theory, with separate initial chapters on measuring detection and evaluating decision criteria. Some other features include: *complete tools for application, including flowcharts, tables, pointers, and software; *student-friendly language; *complete coverage of content area, including both one-dimensional and multidimensional models; *separate, systematic coverage of sensitivity and response bias measurement; *integrated treatment of threshold and nonparametric approaches; *an organized, tutorial level introduction to multidimensional detection theory; *popular discrimination paradigms presented as applications of multidimensional detection theory; and *a new chapter on ideal observers and an updated chapter on adaptive threshold measurement. This up-to-date summary of signal detection theory is both a self-contained reference work for users and a readable text for graduate students and other researchers learning the material either in courses or on their own.