Machine learning models and architectures for biomedical signal processing /
Machine Learning Models and Architectures for Biomedical Signal Processing presents the fundamental concepts of machine learning techniques for bioinformatics in an interactive way. The book investigates how efficient machine and deep learning models can support high-speed processors with reconfigur...
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| Altres autors: | , , , |
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| Format: | Electrònic eBook |
| Idioma: | anglès |
| Publicat: |
London, United Kingdom :
Academic Press,
[2025]
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| Matèries: | |
| Accés en línia: | ScienceDirect |
| Etiquetes: |
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| Sumari: | Machine Learning Models and Architectures for Biomedical Signal Processing presents the fundamental concepts of machine learning techniques for bioinformatics in an interactive way. The book investigates how efficient machine and deep learning models can support high-speed processors with reconfigurable architectures like graphic processing units (GPUs), Field programmable gate arrays (FPGAs), or any hybrid system. This great resource will be of interest to researchers working to increase the efficiency of hardware and architecture design for biomedical signal processing and signal processing techniques. |
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| Descripció física: | 1 online resource (xxiii, 590 pages) : illustrations |
| Bibliografia: | Includes bibliographical references and index. |
| ISBN: | 044322157X 9780443221576 |