Appropriate for courses in System Identification. This book is a comprehensive and coherent description of the theory, methodology and practice of System Identification--the science of building mathematical models of dynamic systems by observing input/output data. It puts the user in focus, giving the necessary background to understand theoretical foundation and emphasizing the practical aspects of the options and choices that face the user. The Second Edition has been updated to include material on subspace methods, non-linear black box models--such as neural networks--and methods that use frequency domain data.