Convergent advances in neural modeling, neuroinformatics, neuromorphic engineering,
materials science, and computer science will soon enable the development and …

Progress in hardware and algorithms for artificial intelligence (AI) has ushered in large
machine learning models and various applications impacting our everyday lives. However …

In the computational intelligence field of study neuromorphic computing is close to reaching
critical mass to enable low power compact hardware systems to perform intelligent cognitive …

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Memristive devices share remarkable similarities to biological synapses, dendrites, and
neurons at both the physical mechanism level and unit functionality level, making the …

This book argues that neuromorphic computing, and particularly the recently emerging
efficient hardware architectures for neuromorphic computing, are of particular significance to …

Neuromorphic computing promises an energy-efficient alternative to traditional digital
processors in handling data-heavy tasks, primarily driven by the development of both …

Memristors have been compared to neurons and synapses, suggesting they would be good
for neuromorphic computing. A change in voltage across a memristor causes a current spike …

The advent of neuromorphic electronics is increasingly revolutionizing the concept of
computation. In the last decade, several studies have shown how materials, architectures …

Modern artificial intelligence (AI) systems, based on von Neumann architecture and classical
neural networks, have a number of fundamental limitations in comparison with the …