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.
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JULIUS S. BENDAT is a mathematical consultant and lecturer.
New practical techniques for nonlinear system research and evaluation
Nonlinear Systems Techniques and Applications provides the most practical techniques currently available for analyzing and identifying nonlinear systems from random data measured at the input and output points of the nonlinear systems. These new techniques require only one-dimensional spectral functions that are much simpler to compute and apply than previous nonlinear procedures. The new results show when and how to replace a wide class of single-input/single-output nonlinear models with simpler equivalent multiple-input/single-output linear models. While other techniques are usually restricted to Gaussian data, the new techniques developed here apply to data with arbitrary probability, correlation, and spectral properties.
Numerous examples used in the book are based on the analysis of real physical data passing through real nonlinear systems in the fields of oceanography, automotive engineering, and biomedical research.
For practicing engineers and scientists involved in aerospace, automotive, biomedical, electrical, mechanical, oceanographic, and other activities concerned with nonlinear system analysis, Nonlinear Systems Techniques and Applications is the essential reference work in the field.
New practical techniques for nonlinear system research and evaluation
Nonlinear Systems Techniques and Applications provides the most practical techniques currently available for analyzing and identifying nonlinear systems from random data measured at the input and output points of the nonlinear systems. These new techniques require only one-dimensional spectral functions that are much simpler to compute and apply than previous nonlinear procedures. The new results show when and how to replace a wide class of single-input/single-output nonlinear models with simpler equivalent multiple-input/single-output linear models. While other techniques are usually restricted to Gaussian data, the new techniques developed here apply to data with arbitrary probability, correlation, and spectral properties.
Numerous examples used in the book are based on the analysis of real physical data passing through real nonlinear systems in the fields of oceanography, automotive engineering, and biomedical research.
For practicing engineers and scientists involved in aerospace, automotive, biomedical, electrical, mechanical, oceanographic, and other activities concerned with nonlinear system analysis, Nonlinear Systems Techniques and Applications is the essential reference work in the field.
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