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Computational Techniques in Neuroscience: (Computational Methods for Industrial Applications)

Computational Techniques in Neuroscience: (Computational Methods for Industrial Applications)

          
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About the Book

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 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.

Table of Contents:
Chapter 1 Dynamic Intuitionistic Fuzzy Weighting Averaging Operator: A Multi-Criteria Decision-Making Technique for the Diagnosis of Brain Tumor Vijay Kumar, H D Arora, Kiran Pal Chapter 2 NEURAL MODELING AND NEURAL COMPUTATION IN MEDICAL APPROACH Simran Singh, Anshika Gupta, Kalpana Chapter 3 Neural networks and Neurodiversity – The Key foundation for Neuroscience Hera Fatma, Harshit Mishra, Kalpana Katiyar Chapter 4 Brain Waves, Neuroimaging (fMRI, EEG, MEG, PET, NIR) Surbhi Kumari, Amit Kumar Dutta Chapter 5 EEG: Concepts, Research-based Analytics, and Applications Rashmi Gupta, Sonu Purohit, Jeetendra Kumar Chapter 6 Classification of gait signals for detection of neurodegenerative diseases using Log-energy entropy and ANN Classifier Prasanna J, S. Thomas George, M.S.P Subathra Chapter 7 An Optimized Text Summarization for Healthcare Analytics using Swarm Intelligence. Rekha Jain, Pratistha Mathur, Manisha Chapter 8 Computer-Aided Diagnosis of neurodegenerative diseases using Discrete Wavelet Transform and Artificial Neural network Prasanna J, S. Thomas George, M.S.P Subathra Chapter 9 EEG Artifact Detection and Removal Techniques: A Brief Review Sandhyalati Behera and Mihir Narayan Mohanty Chapter 10 Analysis of Neural Network and Neuromorphic Computing with hardware- A Survey Manish Bhardwaj, Kailash Nath Tripathi, Yogendra Narayan Prajapati, Analp Pathak Chapter 11 Analysis of Technology Research and ADHD with neurodivergent Reader- A Survey Manish Bhardwaj, Jyoti Sharma, Analp Pathak, Vinay Kumar Sharma, Mayank Tyagi


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Product Details
  • ISBN-13: 9781032461281
  • Publisher: Taylor & Francis Ltd
  • Publisher Imprint: CRC Press
  • Height: 234 mm
  • No of Pages: 224
  • Series Title: Computational Methods for Industrial Applications
  • Weight: 566 gr
  • ISBN-10: 1032461284
  • Publisher Date: 14 Nov 2023
  • Binding: Hardback
  • Language: English
  • Returnable: Y
  • Spine Width: 14 mm
  • Width: 156 mm


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