Machine Learning Models and Architectures for Biomedical Signal Processing

By: Suman Lata Tripathi (Editor), Valentina Emilia Balas (Editor), Mufti Mahmud (Editor), Soumya Banerjee (Editor)

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Paperback | 8 November 2024 | Edition Number 1

At a Glance

Paperback
400 Pages

Dimensions(cm)
23.5 x 19.1

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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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