The purpose of this book is to introduce the reader to the basic theory of signal detection and estimation. It is assumed that the reader has a working knowledge of applied probabil ity and random processes such as that taught in a typical first-semester graduate engineering course on these subjects. This material is covered, for example, in the book by Wong (1983) in this series. More advanced concepts in these areas are introduced where needed, primarily in Chapters VI and VII, where continuous-time problems are treated. This book is adapted from a one-semester, second-tier graduate course taught at the University of Illinois. However, this material can also be used for a shorter or first-tier course by restricting coverage to Chapters I through V, which for the most part can be read with a background of only the basics of applied probability, including random vectors and conditional expectations. Sufficient background for the latter option is given for exam pIe in the book by Thomas (1986), also in this series.
This reference spells out the fundamentals of Augmented with 1024 equations, 138 references and 82 figures and 69 problems, this book provides an introduction to and overview of signal detection...
This volume provides an introduction to signal-detection theory, a subject fundamental to the design of detectors of weak signals in the presence of random noise, and, in particular, to the design of optimal and near optimal receivers of ...
However, before describing the properties of the ROC, it is convenient to introduce the class of Neyman-Pearson tests. 2.4.1 Neyman-Pearson Tests These tests play an important historical and practical role in detection theory.
"For those involved in the design and implementation of signal processing algorithms, this book strikes a balance between highly theoretical expositions and the more practical treatments, covering only those approaches necessary for ...
Covering the fundamentals of detection and estimation theory, this systematic guide describes statistical tools that can be used to analyze, design, implement and optimize real-world systems.
The text also describes the application of hypothesis testing for the detection of signals and the fundamentals required for statistical detection of signals in noise.
Quantum Detection and Estimation Theory
This book embraces the many mathematical procedures that engineers and statisticians use to draw inference from imperfect or incomplete measurements. This book presents the fundamental...
A. Tartakovsky, I. Nikiforov, M. Basseville, Sequential Analysis: Hypothesis Testing and Changepoint Detection (CRC ... 18(4), 1895–1899 (1990) P. Williams, Evaluating the state probabilities of m out of n sliding window detectors.
Throughout the book, the author keeps the needs of practicing engineers firmly in mind.