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Nonlinear Time Series and Signal Processing

  • Book
  • © 1988

Overview

Editors:
  1. R. R. Mohler
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Part of the book series: Lecture Notes in Control and Information Sciences (LNCIS, volume 106)

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Table of contents (10 chapters)

  1. Front Matter

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  2. On the application of kalman filtering to correct errors due to vertical deflections in inertial navigation

    • A. V. Balakrishnan
    Pages 1-9

  3. Filtering and detection problem for nonlinear time series

    • Wojciech J. Kolodziej, Andrzej Pacut
    Pages 10-17

  4. Spectral and bispectral methods for the analysis of nonlinear (non Gaussian) time series signals

    • T. Subba Rao
    Pages 18-42

  5. Bilinear time series: Theory and application

    • Z. Tang, R. R. Mohler
    Pages 43-58

  6. Bivariate bilinear models and their specification

    • Kuldeep Kumar
    Pages 59-74

  7. Non-linear time series modelling in population biology: A preliminary case study

    • H Tong
    Pages 75-87

  8. The akaike information criterion in threshold modelling: Some empirical evidences

    • W. K. Li
    Pages 88-96

  9. Nonlinear time series analysis for dynamical systems of catastrophe type

    • Loren Cobb, Shelemyahu Zacks
    Pages 97-118

  10. Nonlinear processing with Mth-order signals

    • F. J. Bugnon, R. R. Mohler
    Pages 119-129

  11. Stochastic circulatory lymphocyte models

    • Z. H. Farooqi, R. R. Mohler
    Pages 130-145
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Keywords

About this book

This monograph provides a sample of relevant new results on dynamical nonlinear statistical modeling and estimation which forms a basis for more effective signal processing, decision and control. While the research literature is rich in linear Gaussian methodologies, new contributions to the most relevant area of nonlinear and non-Gaussian processes have been scarce. Among the significant areas of application for which such methodologies are needed are: economics, biology, immunology, underwater acoustics, electric power generation, chemical process control, and variable structure systems in general. The latter include adaptive, intelligent, and decomposing mathematical structures or processes. The volume includes ten research papers on theory, computational methods, and applications. Topics include filtering with application to inertial navigation, structural-change detection, bilinear time-series models, bispectral estimation, threshold models, catastrophic models and a generalized eigenstructure method.

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