Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB, 2nd Edition

This revised edition is designed to be a fundamental but practical introduction to the principles and finer intricacies of intelligent computer vision and more generally intelligent measurement systems. It features several significant changes, such as extra computer vision examples (regarding machine learning) over state estimation, with chapters 4 to 7 being largely updated with the latest methods and techniques in classification and supervised learning. The new chapter 5 pays more attention to modern state estimation techniques and the old content of particle filter methods will be discussed in more detail with recent development alongside the new introduction of two kinds of AI state estimation methods (Neural Network and Genetic State Estimation). Further to this, all examples will be rewritten to coincide with refined ideas and updated software, including a new chapter explaining the use and function of PRTools5 for MATLAB.