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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.
When you click on links to various merchants on this site and make a purchase, this can result in this site earning a commission. Affiliate programs and affiliations include, but are not limited to, the eBay Partner Network.