Topics in Non-Gaussian Signal Processing

✍ Scribed by Patrick L. Brockett, Melvin Hinich, Gary R. Wilson (auth.), Edward J. Wegman, Stuart C. Schwartz, John B. Thomas (eds.)

• Publisher: Springer-Verlag New York
• Year: 1989
• Tongue: English
• Leaves: 245
• Edition: 1
• Category: Library

✦ Synopsis

Non-Gaussian Signal Processing is a child of a technological push. It is evident that we are moving from an era of simple signal processing with relatively primitive electronic cir­ cuits to one in which digital processing systems, in a combined hardware-software configura.­ tion, are quite capable of implementing advanced mathematical and statistical procedures. Moreover, as these processing techniques become more sophisticated and powerful, the sharper resolution of the resulting system brings into question the classic distributional assumptions of Gaussianity for both noise and signal processes. This in turn opens the door to a fundamental reexamination of structure and inference methods for non-Gaussian sto­ chastic processes together with the application of such processes as models in the context of filtering, estimation, detection and signal extraction. Based on the premise that such a fun­ damental reexamination was timely, in 1981 the Office of Naval Research initiated a research effort in Non-Gaussian Signal Processing under the Selected Research Opportunities Program.

✦ Table of Contents

Front Matter....Pages i-xii
Front Matter....Pages 1-1
Bispectral Characterization of Ocean Acoustic Time Series: Nonlinearity and Non-Gaussianity....Pages 2-16
Class a Modeling of Ocean Acoustic Noise Processes....Pages 17-28
Statistical Characteristics of Ocean Acoustic Noise Processes....Pages 29-57
Conditionally Linear and Non-Gaussian Processes....Pages 58-72
A Graphical Tool for Distribution and Correlation Analysis of Multiple Time Series....Pages 73-86
Front Matter....Pages 87-87
Comments on Structure and Estimation for NonGaussian Linear Processes....Pages 88-97
Harmonizable Signal Extraction, Filtering and Sampling....Pages 98-117
Fisher Consistency of Am-Estimates of the Autoregression Parameter Using Hard Rejection Filter Cleaners....Pages 118-127
Bayes Least Squares Linear Regression Is Asymptotically Full Bayes: Estimation of Spectral Densities....Pages 128-147
Front Matter....Pages 148-148
Signal Detection for Spherically Exchangeable (Se) Stochastic Processes....Pages 149-167
Contributions to Non-Gaussian Signal Processing....Pages 168-183
Detection of Signals in the Presence of Strong, Signal-Like Interference and Impulse Noise....Pages 184-196
On NonGaussian Signal Detection and Channel Capacity....Pages 197-208
Detection in a Non-Gaussian Environment: Weak and Fading Narrowband Signals....Pages 209-227
Energy Detection in the Ocean Acoustic Environment....Pages 228-235

✦ Subjects

Communications Engineering, Networks