Pattern Recognition and Prediction with Applications to Signal Processing
Pattern Recognition and Prediction with Applications to Signal Processing by David H. Kil is published by the American Institute of Physics and was released on August 1, 1997. This 418-page book is written in English and addresses engineers and researchers involved in fields such as neural networks, image processing, and medical imaging. It begins by exploring the theoretical foundations of pattern recognition and presents an integrated paradigm that combines various elements like preprocessing and feature optimization.
Readers will find a comprehensive examination of pattern recognition and prediction, supported by real-world examples that include financial market prediction and intelligent product design. The book emphasizes a seamless approach to mapping classifier architecture to effective features, making it a valuable resource for those interested in software development and information technology. Through its detailed exploration of these subjects, this edition provides insights into both the theoretical and practical applications of pattern recognition.
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Market: Engineers and researchers in neural networks, image processing, audio/speech, and medical imaging. This book begins by focusing on the theoretical aspect of pattern recognition and introduces an integrated pattern recognition paradigm, which combines preprocessing, low dimensional signal characterization, feature optimization, and mapping classifier architecture to good features in a seamless fashion. Later, the authors reinforce the concepts of pattern recognition and prediction with challenging real- world examples, encompassing financial market prediction, image coding, active and passive sonar processing, chaos modeling, and intelligent product design.
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