Systems identification is a general term used to describe mathematical tools and algorithms that build dynamical models from measured data. Mastering System Identification in 100 Exercises takes readers step by step through a series of MATLAB exercises that teach how to measure and model linear dynamic systems in the presence of nonlinear distortions from a practical point of view. Each exercise is followed by a short discussion illustrating what lessons can be learned by the reader.

The book, with its learn-by-doing approach, also includes:

• State-of-the-art system identification methods, with both time and frequency domain system identification methods-including the pros and cons of each

• Simple writing style with numerous examples and figures

• Downloadable author-programmed MATLAB files for each exercise-with detailed solutions

• Larger projects that serve as potential assignments

Covering both classic and recent measurement and identifying methods, this book will appeal to practicing engineers, scientists, and researchers, as well as master's and PhD students in electrical, mechanical, civil, and chemical engineering.