Model-Based Processing: An Applied Subspace Identification Approach

By James V Candy

This book focuses on presenting the development of models for the design of model-based signal processors (MBSP) using subspace identification techniques to achieve the model-based identification (MBID), as well as incorporating validation and statistical analysis methods to evaluate overall performance. It presents a different approach that incorporates the solution to the system identification problem as the integral part of the model-based signal processor (Kalman filter) that can be applied to a large number of applications, but will have little success unless a reliable model is available or can be adapted to a changing environment. Here, using subspace approaches, it is possible to identify the model very rapidly and incorporate it into a variety of processing problems such as state estimation, tracking, detection, classification, controls, communications to mention a few.

• Format: Hardcover
• Language: English
• ISBN: 1119457769
• ISBN13: 9781119457763
• Release Date: March 2019
• Publisher: Wiley
• Length: 544 Pages
• Weight: 2.20 lbs.
• Dimensions: 1.2" x 6.2" x 9.1"