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Model-Based Processing : An Applied Subspace Identification Approach by Candy J.V is a nonfiction available to read on EtoBox.

What is Model-Based Processing : An Applied Subspace Identification Approach about?

A bridge between the application of subspace-based methods for parameter estimation in signal processing and subspace-based system identification in control systems Model-Based Processing: An Applied Subspace Identification Approach provides expert insight on developing models for designing model-based signal processors (MBSP) employing subspace identification techniques to achieve model-based identification (MBID) and enables readers to evaluate overall performance using validation and statistical analysis methods. Focusing on subspace approaches to system identification problems, this book teaches readers to identify models quickly and incorporate them into various processing problems including state estimation, tracking, detection, classification, controls, communications, and other applications that require reliable models that can be adapted to dynamic environments. The extraction of a model from data is vital to numerous applications, from the detection of submarines to determining the epicenter of an earthquake to controlling an autonomous vehicles—all requiring a fundamental understanding of their underlying processes and measurement instrumentation. Emphasizing real-world

Who reads Model-Based Processing : An Applied Subspace Identification Approach?

Author

Candy J.V

Publisher

John Wiley & Sons, Incorporated

Published

2019

Language

EN

ISBN

9781119457787

Category

nonfiction

Subjects

Engineering, Mathematics, Stem