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This textbook provides a comprehensive understanding of multirate signal processing, focusing on practical applications and real-world examples implemented in Python. The book covers fundamental and advanced topics such as filter banks, sampling theory, and z-domain analysis, making it ideal for graduate-level courses and professionals. Through a combination of theoretical insights and Python-based examples, readers gain both the conceptual understanding and practical skills needed to apply multirate techniques in fields like audio coding, telecommunications, and machine learning. Ancillaries include homework problems, Python code examples, a Github repository with Colab Notebooks, and a chatbot for asking questions and finding answers quickly.
- Offers a detailed, application-focused guide to multirate signal processing, with examples implemented in Python;
- Covers advanced applications in audio, telecommunications, and machine learning;
- Includes Python code examples, a book chatbot, and a Github repository with Colab Notebooks.
List of contents
Introduction.- Introduction to Multirate Signal Processing.- Multiresolution and Filter Banks.- Frequency Response.- Filter Design and Analysis.- Windows and Filter Optimization.- Sampling Theory and Applications.- z-Domain and Effects.- Non-Ideal Filters.- Transforms as Filter Banks.- DCT, Polyphase Representation.- Polyphase Matrices.- The Modified Discrete Cosine Transform (MDCT).- Low Delay Filter Banks.- Optimization of Filter Banks.- Artificial Neural Networks.- Conclusion.
About the author
Gerald Schuller is a full professor at the Institute for Media Technology of the Technical University of Ilmenau, since 2008. He was head of the Audio Coding for Special Applications group of the Fraunhofer Institute for Digital Media Technology in Ilmenau, Germany, since January 2002 until 2008, and is now a member of Fraunhofer IDMT. Before joining the Fraunhofer Institute, he was a Member of Technical Staff at Bell Laboratories, Lucent Technologies, and Agere Systems, a Lucent Spin-off, from 1998 to 2001. There he worked in the Multimedia Communications Research Laboratory. He received his Diplom degree in Electrical Engineering from the Technical University of Berlin in 1989, and his Ph.D. (Dr.-Ing.) degree from the University of Hanover in 1997, studied at the Massachusetts Institute of Technology in 1989/90 and at the Georgia Institute of Technology in 1993. He was Associate Editor of the IEEE Transactions on Speech and Audio Processing from 2002 until 2006, and the IEEE Transactions on Signal Processing from 2006 to 2009, and of the IEEE Transactions on Multimedia since 2008. He is recipient of the 2006 IEEE Best Paper Award in the Audio and Electroacoustics Area. His research interests are in filter banks, audio coding, music signal processing, and deep learning for multimedia.
Summary
This textbook provides a comprehensive understanding of multirate signal processing, focusing on practical applications and real-world examples implemented in Python. The book covers fundamental and advanced topics such as filter banks, sampling theory, and z-domain analysis, making it ideal for graduate-level courses and professionals. Through a combination of theoretical insights and Python-based examples, readers gain both the conceptual understanding and practical skills needed to apply multirate techniques in fields like audio coding, telecommunications, and machine learning. Ancillaries include homework problems, Python code examples, a Github repository with Colab Notebooks, and a chatbot for asking questions and finding answers quickly.
- Offers a detailed, application-focused guide to multirate signal processing, with examples implemented in Python;
- Covers advanced applications in audio, telecommunications, and machine learning;
- Includes Python code examples, a book chatbot, and a Github repository with Colab Notebooks.
