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.

Expanded to cover more advanced applications where statistical properties of data can be nonstationary and the physical systems nonlinear as opposed to only linear. Stresses the practical use and interpretation of analyzed data to solve problems. Special attention is given to bias and random errors involved in desired estimates and the proper interpretation of results from specific applications. Includes numerous case studies concerned with dynamic problems which can occur in a variety of fields.

A timely update of the classic book on the theory and application of random data analysis

First published in 1971, "Random Data" served as an authoritative book on the analysis of experimental physical data for engineering and scientific applications. This "Fourth Edition" features coverage of new developments in random data management and analysis procedures that are applicable to a broad range of applied fields, from the aerospace and automotive industries to oceanographic and biomedical research.

This new edition continues to maintain a balance of classic theory and novel techniques. The authors expand on the treatment of random data analysis theory, including derivations of key relationships in probability and random process theory. The book remains unique in its practical treatment of nonstationary data analysis and nonlinear system analysis, presenting the latest techniques on modern data acquisition, storage, conversion, and qualification of random data prior to its digital analysis. The Fourth Edition also includes: A new chapter on frequency domain techniques to model and identify nonlinear systems from measured input/output random dataNew material on the analysis of multiple-input/single-output linear modelsThe latest recommended methods for data acquisition and processing of random dataImportant mathematical formulas to design experiments and evaluate results of random data analysis and measurement proceduresAnswers to the problem in each chapter

Comprehensive and self-contained, "Random Data, Fourth Edition" is an indispensible book for courses on random data analysis theory and applications at the upper-undergraduate and graduate level. It is also an insightful reference for engineers and scientists who use statistical methods to investigate and solve problems with dynamic data.