COMPUTATIONAL TECHNIQUES IN NEUROSCIENCE.

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 showcas...

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Bibliographic Details
Corporate Author: Taylor & Francis
Other Authors: Malik, Kamal, Sadawarti, Harsh, Sharma, Moolchand, Gupta, Umesh, Tiwari, Prayag
Format: eBook
Language:English
Published: [S.l.] : CRC PRESS, 2023.
Series:Computational methods for industrial applications
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Online Access:Connect to the full text of this electronic book
Description
Summary: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. Features: Focuses on neuron modeling, development, and direction of neural circuits to explain perception, behavior, and biologically inspired intelligent agents for decision making Showcases important aspects such as human behavior prediction using smart technologies and understanding the modeling of nervous systems Discusses nature-inspired algorithms such as swarm intelligence, ant colony optimization, and multi-agent systems Presents information-theoretic, control-theoretic, and decision-theoretic approaches in neuroscience.Includes case studies in functional magnetic resonance imaging (fMRI) and neural data analysis This reference text addresses different applications of computational neuro-sciences using articial 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.
Physical Description:1 online resource.
ISBN:9781000994148
1000994147
9781003398066
1003398065
9781000994216
100099421X