Everything about Neuromorphic computing
Integrated circuit technology
Neuromorphic computing is a computing approach inspired by the human brain's structure and function. It uses artificial neurons to perform computations, mimicking neural systems for tasks such as perception, motor control, and multisensory integration. These systems, implemented in analog, digital, or mixed-mode VLSI, prioritize robustness, adaptability, and learning by emulating the brain’s distributed processing across small computing elements. This interdisciplinary field integrates biology, physics, mathematics, computer science, and electronic engineering to develop systems that emulate the brain’s morphology and computational strategies. Neuromorphic systems aim to enhance energy efficiency and computational power for applications including artificial intelligence, robotics, pattern recognition, and sensory processing. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Neuromorphic computingA 5-minute orientation
- Skim a recent paper: Opportunities for neuromorphic computing algorithms and applicationsInfluential work since 2022
- Pick up a classic book: Neuromorphic and brain-based robotsThe most-reprinted book on the subject
- Read the landmark paper: Memristors with diffusive dynamics as synaptic emulators for neuromorphic computingCited 2,313 times
- Go sideways: Physical neural networkA closely related topic
- Go sideways: Spiking neural networkA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing
Towards spike-based machine intelligence with neuromorphic computing
Physics for neuromorphic computing
Organic electronics for neuromorphic computing
Large-scale neuromorphic computing systems
Neuromorphic computing at scale
Ferroelectric materials for neuromorphic computing
Quantum neuromorphic computing
🆕 Influential since 2022
Opportunities for neuromorphic computing algorithms and applications
2022 roadmap on neuromorphic computing and engineering
Dynamical memristors for higher-complexity neuromorphic computing
Experimental demonstration of highly reliable dynamic memristor for artificial neuron and neuromorphic computing
Reconfigurable halide perovskite nanocrystal memristors for neuromorphic computing
📚 Books worth reading
Neuromorphic and brain-based robotsJeffrey L. Krichmar · 2011
Brain vs computerJ. P. Fillard · 2017
Neuromorphic SystemsEuropean Workshop on Neurmorphic Systems 1997 (University of Stirling) · 1998
Neuromorphic systems engineeringTor Sverre Lande · 1998
Advances In Neuromorphic Memristor Science And ApplicationsRobert Kozma · 2012
Vision Vol. 19Jeanny Herault · 2009
The Making of a Neuromorphic Visual SystemChristoph Rasche · 2004- 📕Neuromorphic and Bio-Inspired Engineered SystemsS.C. Liu · 2007
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- Physical neural network A physical neural network is a type of artificial neural network in which an electrically adjustable material is used to emulate the function of a neural…
- Spiking neural network Spiking neural networks (SNNs) are artificial neural networks (ANN) that mimic natural neural networks. These models leverage timing of discrete spikes…
- Cognitive computer A cognitive computer is a computer that hardwires artificial intelligence and machine learning algorithms into an integrated circuit that closely reproduces…
- SpiNNaker SpiNNaker (spiking neural network architecture) is a massively parallel, manycore supercomputer architecture designed by the Advanced Processor Technologies…
- Artificial neuron An artificial neuron is a mathematical function conceived as a model of a biological neuron in a neural network. The artificial neuron is the elementary…
- Massimiliano Versace Massimiliano Versace (born 21 December 1972) is an Italian-American artificial intelligence researcher and entrepreneur. He co-founded Neurala, a Boston-based…
- Caravelli-Traversa-Di Ventra equation The Caravelli-Traversa-Di Ventra equation (CTDV) is a closed-form equation to the evolution of networks of memristors. It was derived by Francesco Caravelli…
- Memristor A memristor (/ˈmɛmrɪstər/; a portmanteau of memory resistor) is a non-linear two-terminal electrical component relating electric charge and magnetic flux…