RRAM based neuromorphic algorithms

01/12/2019

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This submission is a report on RRAM based neuromorphic algorithms. This report basically gives an overview of the algorithms implemented on neuromorphic hardware with crossbar array of RRAM synapses. This report mainly talks about the work on deep neural network to spiking neural network conversion and its significance.

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RRAM based neuromorphic algorithms

Spiking Neural Network Equalization for IM/DD Optical Communication

MaD: Mapping and debugging framework for implementing deep neural network onto a neuromorphic chip with crossbar array of synapses

Brian2Loihi: An emulator for the neuromorphic chip Loihi using the spiking neural network simulator Brian

Time-coded Spiking Fourier Transform in Neuromorphic Hardware

An Efficient and Accurate Memristive Memory for Array-based Spiking Neural Networks

A Spiking Neural Network Emulating the Structure of the Oculomotor System Requires No Learning to Control a Biomimetic Robotic Head

SuperNeuro: A Fast and Scalable Simulator for Neuromorphic Computing

RRAM based neuromorphic algorithms

Related Research

Spiking Neural Network Equalization for IM/DD Optical Communication

MaD: Mapping and debugging framework for implementing deep neural network onto a neuromorphic chip with crossbar array of synapses

Brian2Loihi: An emulator for the neuromorphic chip Loihi using the spiking neural network simulator Brian

Time-coded Spiking Fourier Transform in Neuromorphic Hardware

An Efficient and Accurate Memristive Memory for Array-based Spiking Neural Networks

A Spiking Neural Network Emulating the Structure of the Oculomotor System Requires No Learning to Control a Biomimetic Robotic Head

SuperNeuro: A Fast and Scalable Simulator for Neuromorphic Computing