System identification theory 2nd edition

Summary: The field's leading text, now completely updated. Modeling dynamical systems - theory, methodology, and applications. Lennart Ljung's System Identification: Theory for the User is a complete, coherent description of the theory, methodology, and practice of System Identification.

This completely revised Second Edition introduces subspace methods, methods that utilize frequency domain data, and general non-linear black box methods, including neural networks and neuro-fuzzy modeling. Ljung combines careful mathematics, a practical understanding of real-world applications, and extensive exercises. He introduces both black-box and tailor-made models of linear as well as non-linear systems, and he describes principles, properties, and algorithms for a variety of identification techniques: Nonparametric time-domain and frequency-domain methods.

We're sorry! We don't recognize your username or password. Please try again. The work is protected by local and international copyright laws and is provided solely for the use of instructors in teaching their courses and assessing student learning. You have successfully signed out and will be required to sign back in should you need to download more resources. System Identification: Theory for the User, 2nd Edition. Lennart Ljung, Linkoping University, Sweden. Overview Features Contents Order Overview.

Description Appropriate for courses in System Identification. It has been translated into Russian and Chinese. Table of Contents 1. Time-Invariant Linear Systems. Modeling dynamical systems — theory, methodology, and applications. He introduces both black-box and tailor-made models of linear as well as non-linear systems, and he describes principles, properties, and algorithms for a variety of identification techniques: Nonparametric time-domain and frequency-domain methods.

Parameter estimation methods in a general prediction error setting. Frequency domain data and frequency domain interpretations. Asymptotic analysis of parameter estimates. Linear regressions, iterative search methods, and other ways to compute estimates.

Recursive adaptive estimation techniques. Show and hide more. Table of contents Product information. Introduction I.

Systems and Models 2. Time-Invariant Linear Systems 3. Simulation and Prediction 4.