Yi Y. Neuromorphic Computing 2023

Textbook in PDF format

Dive into the cutting-edge world of Neuromorphic Computing, a groundbreaking volume that unravels the secrets of brain-inspired computational paradigms. Spanning neuroscience, artificial intelligence, and hardware design, this book presents a comprehensive exploration of neuromorphic systems, empowering both experts and newcomers to embrace the limitless potential of brain-inspired computing. Discover the fundamental principles that underpin neural computation as we journey through the origins of neuromorphic architectures, meticulously crafted to mimic the brain’s intricate neural networks. Unlock the true essence of learning mechanisms – unsupervised, supervised, and reinforcement learning – and witness how these innovations are shaping the future of artificial intelligence.
End-to-End Benchmarking of Chiplet-Based In-Memory Computing
Implementation of Associative Memory Learning in Mobile Robots Using Neuromorphic Computing
Study of RRAM-Based Binarized Neural Networks Inference Accelerators Using an RRAM Physics-Based Compact Model
Enabling Neuromorphic Computing for Artificial Intelligence with Hardware-Software Co-Design
Neuromorphic Computing between Reality and Future Needs
A Study of the Comparison between Artificial Neural Networks, Logistic Regression and Similarity Weighted Instance-Based Learning in Modeling and Predicting Trends in Deforestation
Spiking Neural Encoding and Hardware Implementations for Neuromorphic Computing
Cortical Columns Computing Systems: Microarchitecture Model, Functional Building Blocks, and Design Tools
Artificial Intelligence Approaches for Studying the pp Interactions at High Energy Using Adaptive Neuro-Fuzzy Interface System
Study of Approaches to Predict Personality Using Digital Twin
Scaling Subspace-Driven Approaches Using Information Fusion