Energy-Efficient CMOS Memristive Synapses for Mixed-Signal Neuromorphic System-on-a-Chip

no code implementations • 7 Feb 2018 • Vishal Saxena, Xinyu Wu, Kehan Zhu

Emerging non-volatile memory (NVM), or memristive, devices promise energy-efficient realization of deep learning, when efficiently integrated with mixed-signal integrated circuits on a CMOS substrate.

A CMOS Spiking Neuron for Dense Memristor-Synapse Connectivity for Brain-Inspired Computing

no code implementations • 2 Jun 2015 • Xinyu Wu, Vishal Saxena, Kehan Zhu

Neuromorphic systems that densely integrate CMOS spiking neurons and nano-scale memristor synapses open a new avenue of brain-inspired computing.

Homogeneous Spiking Neuromorphic System for Real-World Pattern Recognition

no code implementations • 2 Jun 2015 • Xinyu Wu, Vishal Saxena, Kehan Zhu

A neuromorphic chip that combines CMOS analog spiking neurons and memristive synapses offers a promising solution to brain-inspired computing, as it can provide massive neural network parallelism and density.

A CMOS Spiking Neuron for Brain-Inspired Neural Networks with Resistive Synapses and In-Situ Learning

no code implementations • 28 May 2015 • Xinyu Wu, Vishal Saxena, Kehan Zhu, Sakkarapani Balagopal

Nanoscale resistive memories are expected to fuel dense integration of electronic synapses for large-scale neuromorphic system.