Signal Processing and Machine Learning with Applications
Richter, Michael M., Paul, Sheuli
The authors offer a comprehensive guide to machine learning applied to signal processing and recognition problems, and then discuss real applications in domains such as speech processing and biomedical signal processing, with a focus on handling noise. This textbook is intended for advanced undergraduate and graduate students of computer science and engineering.
Prof. Michael M. Richter completed his PhD on mathematical logic at the University of Freiburg, and his Habilitation in mathematics at the University of Tübingen. He taught at the University of Texas at Austin and at RWTH Aachen, in addition to numerous visiting professorships. Most recently he held a chair in computer science at the University of Kaiserslautern, where he was also the founding scientific director of the DFKI (German Research Center for Artificial Intelligence). He is currently an adjunct professor at the University of Calgary. He has taught, researched, and published extensively in the areas of mathematical logic and artificial intelligence. Prof. Richter is one of the pioneers of case-based reasoning: he founded the leading European event on the subject, he led many of the key academic research projects, and he demonstrated the real-world viability of the approach with successful commercial products.
Dr. Sheuli Paul completed her PhD on a dynamic automatic noisy speech recognition system in Kaiserslautern. Her interests include speech recognition and signal processing.
Prof. Michael M. Richter在弗賴堡大學完成了他的數學邏輯博士學位，並在圖賓根大學獲得了數學的資格教授資格。他曾在德克薩斯大學奧斯汀分校和亞琛工業大學任教，並擔任過多個訪問教授職位。最近，他在凱撒斯勞滕大學擔任計算機科學教授，同時也是德國人工智能研究中心（DFKI）的創始科學主任。他目前是卡爾加里大學的兼職教授。他在數學邏輯和人工智能領域有豐富的教學、研究和出版經驗。Richter教授是案例推理的先驅之一：他創辦了該領域的領先歐洲活動，領導了許多重要的學術研究項目，並通過成功的商業產品展示了這種方法的實際可行性。
Dr. Sheuli Paul在凱撒斯勞滕完成了她的博士學位，研究方向是動態自動噪聲語音識別系統。她的興趣包括語音識別和信號處理。