Nonlinear System Techniques and Applications
Rights Contact Login For More Details
More About This Title Nonlinear System Techniques and Applications
English
New practical techniques for nonlinear system research andevaluation
Nonlinear Systems Techniques and Applications provides the mostpractical techniques currently available for analyzing andidentifying nonlinear systems from random data measured at theinput and output points of the nonlinear systems. These newtechniques require only one-dimensional spectral functions that aremuch simpler to compute and apply than previous nonlinearprocedures. The new results show when and how to replace a wideclass of single-input/single-output nonlinear models with simplerequivalent multiple-input/single-output linear models. While othertechniques are usually restricted to Gaussian data, the newtechniques developed here apply to data with arbitrary probability,correlation, and spectral properties.
Numerous examples used in the book are based on the analysis ofreal physical data passing through real nonlinear systems in thefields of oceanography, automotive engineering, and biomedicalresearch.
For practicing engineers and scientists involved in aerospace,automotive, biomedical, electrical, mechanical, oceanographic, andother activities concerned with nonlinear system analysis,Nonlinear Systems Techniques and Applications is the essentialreference work in the field.
Nonlinear Systems Techniques and Applications provides the mostpractical techniques currently available for analyzing andidentifying nonlinear systems from random data measured at theinput and output points of the nonlinear systems. These newtechniques require only one-dimensional spectral functions that aremuch simpler to compute and apply than previous nonlinearprocedures. The new results show when and how to replace a wideclass of single-input/single-output nonlinear models with simplerequivalent multiple-input/single-output linear models. While othertechniques are usually restricted to Gaussian data, the newtechniques developed here apply to data with arbitrary probability,correlation, and spectral properties.
Numerous examples used in the book are based on the analysis ofreal physical data passing through real nonlinear systems in thefields of oceanography, automotive engineering, and biomedicalresearch.
For practicing engineers and scientists involved in aerospace,automotive, biomedical, electrical, mechanical, oceanographic, andother activities concerned with nonlinear system analysis,Nonlinear Systems Techniques and Applications is the essentialreference work in the field.
English
JULIUS S. BENDAT is a mathematical consultant and lecturer.
English
Linear Systems, Random Data.
Zero-Memory Nonlinear Systems.
Direct and Reverse MI/SO Techniques for Analysis and Identificationof Nonlinear Systems.
Parallel Linear and Nonlinear Systems.
Determination of Physical Parameters with Memory in NonlinearSystems.
Nonlinear System Response Properties of a Naval Frigate fromMeasured Ocean Engineering Data.
Nonlinear System Response Properties of a Naval Barge from MeasuredOcean Engineering Data.
Bilinear and Trilinear Systems.
Input/Output Relations for Bilinear and Trilinear Systems.
References.
Index.
Glossary of Symbols.
Zero-Memory Nonlinear Systems.
Direct and Reverse MI/SO Techniques for Analysis and Identificationof Nonlinear Systems.
Parallel Linear and Nonlinear Systems.
Determination of Physical Parameters with Memory in NonlinearSystems.
Nonlinear System Response Properties of a Naval Frigate fromMeasured Ocean Engineering Data.
Nonlinear System Response Properties of a Naval Barge from MeasuredOcean Engineering Data.
Bilinear and Trilinear Systems.
Input/Output Relations for Bilinear and Trilinear Systems.
References.
Index.
Glossary of Symbols.
English
"...of extreme value to scientists and engineers engaged in nonlinear system identification...a valuable contribution to the emerging field of nonlinear system identification due to its clear treatment of mathematical theory and engineering applications." (International Journal of Robust and Nonlinear Control, Vol. 11, July 2001)
