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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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Bibliographic Details
Corporate Author: ScienceDirect (Online service)
Other Authors: Tripathi, Suman Lata (Editor), Balas, Valentina Emilia (Editor), Mahmud, Mufti (Editor), Banerjee, Soumya (Editor)
Format: eBook
Language:English
Published: London, United Kingdom : Academic Press, [2025]
Subjects:
Machine learning.
Bioinformatics.
Medical informatics.
Signal processing > Digital techniques > Data processing.
Biomedical engineering.
Apprentissage automatique.
Bio-informatique.
Médecine > Informatique.
Traitement du signal > Techniques numériques > Informatique.
Génie biomédical.
biomedical engineering.
Electronic books.
Online Access:Connect to the full text of this electronic book
Description
Summary: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.
Physical Description:1 online resource
Bibliography:Includes bibliographical references and index
ISBN:044322157X
9780443221576