Nonlinear Time Series and Signal Processing

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 re...

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Bibliographic Details
Other Authors: Mohler, Ronald R. (Editor)
Format: eBook
Language:English
Published: Berlin, Heidelberg Springer Berlin Heidelberg 1988, 1988
Edition:1st ed. 1988
Series:Lecture Notes in Control and Information Sciences
Subjects:
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
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100 1 |a Mohler, Ronald R.  |e [editor] 
245 0 0 |a Nonlinear Time Series and Signal Processing  |h Elektronische Ressource  |c edited by Ronald R. Mohler 
250 |a 1st ed. 1988 
260 |a Berlin, Heidelberg  |b Springer Berlin Heidelberg  |c 1988, 1988 
300 |a V, 150 p. 9 illus  |b online resource 
505 0 |a Contents: On the Application of Kalman Filtering to Correct Errors due to Vertical Deflection in Inertial Navigation -- Filtering and Detection Problems for Nonlinear Time Series -- Spectral and Bispectral Methods for the Analysis of Nonlinear (Non-Gaussian) Time-Series Signals -- Bilinear Time Series: Theory and Application -- Bivariate Bilinear Models and Their Identification -- Nonlinear Time Series Modelling in Population Biology -- The Akaike Information Criterion in Threshold Modelling -- Nonlinear Time Series Analysis for Dynamical Systems of Catastrophe Type -- Nonlinear Processing with M-th Order Signals -- Stochastic Circulatory Lymphocyte Models 
653 |a Control, Robotics, Automation 
653 |a Calculus of Variations and Optimization 
653 |a Control theory 
653 |a Systems Theory, Control 
653 |a System theory 
653 |a Control engineering 
653 |a Robotics 
653 |a Mathematical optimization 
653 |a Automation 
653 |a Calculus of variations 
041 0 7 |a eng  |2 ISO 639-2 
989 |b SBA  |a Springer Book Archives -2004 
490 0 |a Lecture Notes in Control and Information Sciences 
028 5 0 |a 10.1007/BFb0044270 
856 4 0 |u https://doi.org/10.1007/BFb0044270?nosfx=y  |x Verlag  |3 Volltext 
082 0 |a 629.8 
520 |a 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