This is a complete, coherent description of the theory, methodology and practice of System Identification. The completely revised Second Edition introduces subspace methods, methods that utilize frequency domain data, and these key non-linear black box methods: neural networks, wavelet transforms, neuro-fuzzy modeling and hinging hyperplanes.KEY TOPICS:Leader in the field Lennart Ljung introduces systems and models, time-invariant linear systems, time-varying and nonlinear systems. He presents several approaches to system identification, including nonparametric time- and frequency-domain methods; parameter estimation; convergence and consistency; asymptotic distribution of parameter estimates; linear regressions, iterative search and recursive estimation. He also presents detailed coverage of key issues that can make or break system identification projects: defining objectives, designing experiments, selecting criteria, and controlling the bias distribution of transfer-function estimates.MARKET:For all engineering and control systems professionals, faculty and students.

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LENNART LJUNG is Professor of the Chair of Automatic Control in the Department of Electrical Engineering, Linkšping University, Sweden. He is the author of nine books and over 100 articles in refereed international journals, as well as the author of the field's leading software package, System Identification Toolbox for MATLAB.

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