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By: Harsh Sadawarti (Edited by) , Kamal Malik (Edited by) , Moolchand Sharma (Edited by) , Prayag Tiwari (Edited by) , Umesh Gupta (Edited by)
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The text discusses the techniques of deep learning and machine learning in the field of neuroscience, engineering approaches to study the brain structure and dynamics, convolutional networks for fast, energy-efficient neuromorphic computing, and reinforcement learning in feedback control. It showcases case studies in neural data analysis.
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This reference text addresses different applications of computational neuro-sciences using arti?cial intelligence, deep learning, and other machine learning techniques to ?ne-tune the models, thereby solving the real-life problems prominently. It will further discuss important topics such as neural rehabili-tation, brain-computer interfacing, neural control, neural system analysis, and neurobiologically inspired self-monitoring systems. It will serve as an ideal reference text for graduate students and academic researchers in the ?elds of electrical engineering, electronics and communication engineering, computer engineering, information technology, and biomedical engineering.
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