Primer to Neuromorphic Computing highlights critical and ongoing research into the diverse applications of neuromorphic computing. It includes an overview of primary scientific concepts for the research topic of neuromorphic computing, such as neurons as computational units, artificial intelligence, machine learning, and neuromorphic models. It also discusses the fundamental design method and organization of neuromorphic architecture. Hardware for neuromorphic systems can be developed by exploiting the magnetic properties of different materials. These systems are more energy efficient and enable faster computation . Magnetic tunnel junctions and magnetic textures can be employed to act as neurons and synapses. Neuromorphic systems have general intelligence like humans as they can apply knowledge gained in one domain to other domains.
1. Primer to Neuromorphic Computing - p. i 2. Cover image - p. i 3. Title page - p. i 4. Table of Contents - p. i 5. Copyright - p. iv 6. Contributors - p. ix 7. Chapter 1 Neuromorphic computing for machine learning: An overview - p. 1 8. Chapter 2 Designing of GAN for a real-time image processing in neuromorphic system - p. 21 9. Chapter 3 Review of existing neuromorphic systems - p. 45 10. Chapter 4 Neuromorphic system for cardiovascular disorders - p. 67 11. Chapter 5 Neuromorphic system for real-time healthcare applications - p. 83 12. Chapter 6 Neomorphic home automation systems - p. 97 13. Chapter 7 Neuromorphic systems for real-time image processing - p. 127 14. Chapter 8 Real-time visual data processing using neuromorphic systems - p. 161 15. Chapter 9 Future prospective of neuromorphic computing in artificial intelligence_ A review, methods, and challenges - p. 185 16. Chapter 10 Neuroscience-inspired facial mask recognition using MobileNet and computer vision in real-time video streaming - p. 199 17. Chapter 11 A neuroinspired journey: Tracing the evolution and objectives of neuromorphic systems - p. 215 18. Chapter 12 Deploying shark smell optimization algorithm with neuromorphic computing for prediction of COVID-19 disease - p. 239 19. Index - p. 257
Primer to Neuromorphic Computing highlights critical and ongoing research into the diverse applications of neuromorphic computing. It includes an overview of primary scientific concepts for the research topic of neuromorphic computing, such as neurons as computational units, artificial intelligence, machine learning, and neuromorphic models. It also discusses the fundamental design method and organization of neuromorphic architecture. Hardware for neuromorphic systems can be developed by exploiting the magnetic properties of different materials. These systems are more energy efficient and enable faster computation . Magnetic tunnel junctions and magnetic textures can be employed to act as neurons and synapses. Neuromorphic systems have general intelligence like humans as they can apply knowledge gained in one domain to other domains.
1. Primer to Neuromorphic Computing - p. i 2. Cover image - p. i 3. Title page - p. i 4. Table of Contents - p. i 5. Copyright - p. iv 6. Contributors - p. ix 7. Chapter 1 Neuromorphic computing for machine learning: An overview - p. 1 8. Chapter 2 Designing of GAN for a real-time image processing in neuromorphic system - p. 21 9. Chapter 3 Review of existing neuromorphic systems - p. 45 10. Chapter 4 Neuromorphic system for cardiovascular disorders - p. 67 11. Chapter 5 Neuromorphic system for real-time healthcare applications - p. 83 12. Chapter 6 Neomorphic home automation systems - p. 97 13. Chapter 7 Neuromorphic systems for real-time image processing - p. 127 14. Chapter 8 Real-time visual data processing using neuromorphic systems - p. 161 15. Chapter 9 Future prospective of neuromorphic computing in artificial intelligence_ A review, methods, and challenges - p. 185 16. Chapter 10 Neuroscience-inspired facial mask recognition using MobileNet and computer vision in real-time video streaming - p. 199 17. Chapter 11 A neuroinspired journey: Tracing the evolution and objectives of neuromorphic systems - p. 215 18. Chapter 12 Deploying shark smell optimization algorithm with neuromorphic computing for prediction of COVID-19 disease - p. 239 19. Index - p. 257
