Description
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 artificial intelligence, deep learning, and other machine learning techniques to fine-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 fields 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
