Detection Theory —— Applications and Digital Signal Processing

----- 检测理论

ISBN: 9780849304347 出版年：2017 页码：340 Hippenstiel, Ralph D CRC Press

INTRODUCTION General Philosophy Detection and Estimation Philosophy Description of Spaces involved in the Decision Summary REVIEW OF DETERMINISTIC AND RANDOM SYSTEM AND SIGNAL CONCEPTS Some Mathematical and Statistical Background Systems and Signals (Deterministic and Random) Transformation of Random Variables Summary INTRODUCTION TO SIGNAL PROCESSING Introduction Data Structure and Sampling Discrete-Time Transformations Filtering Finite Impulse Response Filter The Fast Fourier Transform Fast Correlation Periodogram (Power Spectral Density Estimate) Wavelets Summary HYPOTHESIS TESTING Introduction Bayes Detection Maximum A Posteriori (MAP) Detection Maximum Likelihood (ML) Criterion Minimum Probability of Error Criterion Min-Max Criterion Neyman-Pearson Criterion Multiple Hypothesis Testing Composite Hypothesis Testing Receiver Operator Characteristic Curves and Performance Summary NON-PARAMETRIC AND SEQUENTIAL LIKELIHOOD RATIO DETECTORS Introduction Non-Parametric Detection Wilcoxon Detector Sequential Detection Summary DETECTION OF SIGNALS IN GAUSSIAN WHITE NOISE Introduction The Binary Detection Problem Matched Filters Matched Filter Approach M-ary Communication Systems Detection of Signals with Random Parameters Multiple Pulse Detection Summary DETECTION OF SIGNALS IN COLORED GAUSSIAN NOISE Introduction Series Representation Derivation of the Correlator Structure Using an Arbitrary Complete Ortho-Normal (C.O.N.) Set Gram-Schmidt Procedure Detection of a Known Signal in Additive White Gaussian Noise Using the Gram-Schmidt Procedure Series Expansion for Continuous Time Detection for Colored Gaussian Noise Detection of Known Signals in Additive Colored Gaussian Noise Discrete Time Detection - Known Signals Embedded in Colored Gaussian Noise Summary ESTIMATION Introduction Basic Estimation Schemes Properties of Estimators Cramer-Rao Bound Waveform Estimation Summary APPLICATIONS TO DETECTION, PARAMETER ESTIMATION, AND CLASSIFICATION Introduction The Periodogram and the Spectrogram Correlation Instantaneous Correlation Function, Wignerville Distribution, Spectral Correlation, and the Ambiguity Function Cyclo-Stationary Processing Higher Order Moments and Poly-Spectra Coherence Processing Wavelet Processing Adaptive Techniques Summary APPENDICES Probability, Random Processes and Systems Signals and Transforms Mathematical Structures Some Mathematical Expressions and Moments of Probability Density Function Wavelet Transforms INDEX