مقدمه‌ای بر شناسایی الگو: رویکردی مبتنی بر متلب

An accompanying manual to Theodoridis/Koutroumbas, Pattern Recognition, that includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition. \*Matlab code and descriptive summary of the most common methods and algorithms in Theodoridis/Koutroumbas, Pattern Recognition 4e. \*Solved examples in Matlab, including real-life data sets in imaging and audio recognition \*Available separately or at a special package price with the main text (ISBN for package: 978-0-12-374491-3) Introduction to Pattern Recognition: A Matlab Approach is an accompanying manual to Theodoridis/Koutroumbas'Pattern Recognition. It includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition. This text is designed for electronic engineering, computer science, computer engineering, biomedical engineering and applied mathematics students taking graduate courses on pattern recognition and machine learning as well as R&D engineers and university researchers in image and signal processing/analyisis, and computer vision. Matlab code and descriptive summary of the most common methods and algorithms in Theodoridis/Koutroumbas, Pattern Recognition, Fourth Edition Solved examples in Matlab, including real-life data sets in imaging and audio recognition Available separately or at a special package price with the main text (ISBN for package: 978-0-12-374491-3) Introduction to Pattern A Matlab Approach is an accompanying manual to Theodoridis/Koutroumbas' Pattern Recognition. It includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition. This text is designed for electronic engineering, computer science, computer engineering, biomedical engineering and applied mathematics students taking graduate courses on pattern recognition and machine learning as well as R&D engineers and university researchers in image and signal processing/analyisis, and computer vision. An accompanying manual to Theodoridis/Koutroumbas, Pattern Recognition, that includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition.

*Matlab code and descriptive summary of the most common methods and algorithms in Theodoridis/Koutroumbas, Pattern Recognition 4e.
*Solved examples in Matlab, including real-life data sets in imaging and audio recognition
*Available separately or at a special package price with the main text (ISBN for package: 978-0-12-374491-3) I have read the first chapter so far, however i have found that the book is so practical. I have passed machine learning in the school and i can say that this book a good snapshot of that subject. The most important thing is that the book includes lots of matlab codes which really help the readers understand the concept of the application of different classifiers in a practical way by solving vary applicable examples throughout the book. This is an accompanying manual to "Theodoridis/Koutroumbas, Pattern Recognition", that includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition. It also includes Matlab code and descriptive summary of the most common methods and algorithms in "Theodoridis/Koutroumbas, Pattern Recognition 4e" Classifiers based on Bayes decision theory Classifiers based on cost function optimization Data transformation : feature generation and dimensionality reduction Feature selection Template matching Hidden Markov models Clustering Appendix.