A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks | Paper Citation Record

Observation 78078dde-b690-4b6e-b1e1-be7a35c3b6ee · outbound

This paper cites Edge intelligence through in-sensor and near-sensor computing for the artificial intelligence of things,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Edge intelligence through in-sensor and near-sensor computing for the artificial intelligence of things,

Reference 1

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Observation 0b83ba21-322e-48c5-b556-0ced1dfd92cd · outbound

This paper cites Networks of spiking neurons: the third generation of neural network models,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Networks of spiking neurons: the third generation of neural network models,

Reference 2

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This paper cites A Survey of Neuromorphic Computing and Neural Networks in Hardware.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks A Survey of Neuromorphic Computing and Neural Networks in Hardware

Reference 3

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This paper cites Loihi: A Neuromorphic Manycore Processor with On-Chip Learning,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Loihi: A Neuromorphic Manycore Processor with On-Chip Learning,

Reference 4

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This paper cites TrueNorth: Design and Tool Flow of a 65 mW 1 Million Neuron Programmable Neurosynaptic Chip,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks TrueNorth: Design and Tool Flow of a 65 mW 1 Million Neuron Programmable Neurosynaptic Chip,

Reference 5

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This paper cites SpiNNaker: A 1-W 18-Core System-on-Chip for Massively-Parallel Neural Network Simulation,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks SpiNNaker: A 1-W 18-Core System-on-Chip for Massively-Parallel Neural Network Simulation,

Reference 6

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This paper cites A 65k-neuron 73-Mevents/s 22-pJ/event asynchronous micro-pipelined integrate-and-fire array transceiver,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks A 65k-neuron 73-Mevents/s 22-pJ/event asynchronous micro-pipelined integrate-and-fire array transceiver,

Reference 7

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Observation 0bafc7e1-7fe8-4e4a-8c37-0a3f67117c7d · outbound

This paper cites Spike timing–dependent plasticity: a hebbian learning rule,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Spike timing–dependent plasticity: a hebbian learning rule,

Reference 8

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Observation 89f5d90a-3426-4578-9cf1-d8f3b071882a · outbound

This paper cites Neuromorphic electronic systems,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Neuromorphic electronic systems,

Reference 9

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This paper cites Memory and Information Processing in Neuromorphic Systems,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Memory and Information Processing in Neuromorphic Systems,

Reference 10

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Observation b0ae036f-50c8-48c1-8de5-fece32ea9299 · outbound

This paper cites A reconfigurable on-line learning spiking neuromorphic processor comprising 256 neurons and 128k synapses,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks A reconfigurable on-line learning spiking neuromorphic processor comprising 256 neurons and 128k synapses,

Reference 11

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This paper cites Exploiting inherent error resiliency of deep neural networks to achieve extreme energy eﬀiciency through mixed-signal neurons,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Exploiting inherent error resiliency of deep neural networks to achieve extreme energy eﬀiciency through mixed-signal neurons,

Reference 12

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Observation be00893e-f213-4e06-882f-654db0bc5e46 · outbound

This paper cites Neuromorphic analog circuits for robust on-chip always-on learning in spiking neural networks.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Neuromorphic analog circuits for robust on-chip always-on learning in spiking neural networks

Reference 13

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Observation a7064443-4751-43f9-b27d-e638b11f79d3 · outbound

This paper cites Variation-tolerant hardware synthesis of spiking neural networks,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Variation-tolerant hardware synthesis of spiking neural networks,

Reference 14

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This paper cites Training Spiking Neural Networks Using Lessons From Deep Learning.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Training Spiking Neural Networks Using Lessons From Deep Learning

Reference 15

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This paper cites Shaping the learning landscape in neural networks around wide flat minima,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Shaping the learning landscape in neural networks around wide flat minima,

Reference 16

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Observation 807393f7-5f52-4d73-98bf-1d5f993bd8ac · outbound

This paper cites Gerstner, W.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Gerstner, W

Reference 17

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Observation 5264294e-9643-4051-bd81-abc7c4a23fe5 · outbound

This paper cites Genesis: A system for simulating neural networks,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Genesis: A system for simulating neural networks,

Reference 18

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Observation e4e5ce12-b017-4ec9-8f4a-4c9976b1e912 · outbound

This paper cites The neuron simulation environment,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks The neuron simulation environment,

Reference 19

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This paper cites Ermentrout, Simulating, Analyzing, and Animating Dynamical Systems: A Guide to XPPAUT for Researchers and Students.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Ermentrout, Simulating, Analyzing, and Animating Dynamical Systems: A Guide to XPPAUT for Researchers and Students

Reference 20

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Observation 4590ca59-de5f-4e29-9c50-8c52077be7d3 · outbound

This paper cites Csim: A neural simulation environment for modeling the dynamics of spiking neuron networks,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Csim: A neural simulation environment for modeling the dynamics of spiking neuron networks,

Reference 21

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This paper cites Exact simulation of integrate-and-fire models with synaptic conductances,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Exact simulation of integrate-and-fire models with synaptic conductances,

Reference 22

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This paper cites Nest (neural simulation tool),.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Nest (neural simulation tool),

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This paper cites On the performance of voltage stepping for the simulation of adaptive, nonlinear integrate-and-fire neuronal networks,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks On the performance of voltage stepping for the simulation of adaptive, nonlinear integrate-and-fire neuronal networks,

Reference 24

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This paper cites A large-scale model of the functioning brain,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks A large-scale model of the functioning brain,

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A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Ncs: A framework for simulating large- scale, biologically realistic neural networks,

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A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Mosaic: in-memory computing and routing for small-world spike-based neuromorphic systems,

Reference 27

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A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks The neuron book,

Reference 28

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A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Simulation of networks of spiking neurons: A review of tools and strategies,

Reference 29

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A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks A floating gate and its application to memory devices,

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A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks A floating-gate MOS learning array with locally computed weight updates,

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A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Floating Gate Synapses With Spike-Time- Dependent Plasticity,

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A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Temporally learning floating-gate VLSI synapses,

Reference 33

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This paper cites Implementation of multilayer perceptron network with highly uniform passive memristive crossbar circuits,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Implementation of multilayer perceptron network with highly uniform passive memristive crossbar circuits,

Reference 34

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A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks An analytical MOS transistor model valid in all regions of operation and dedicated to low-voltage and low-current applications,

Reference 35

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This paper cites Modeling, simulation and implementation of circuit elements in an open-source tool set on the FPAA,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Modeling, simulation and implementation of circuit elements in an open-source tool set on the FPAA,

Reference 36

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A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Analysis and verilog-a modeling of floating-gate transistors,

Reference 37

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A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Integrated Floating-Gate Programming Environment for System-Level ICs,

Reference 38

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A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Modeling and analysis of analog non-volatile devices for compute-in-memory applications,

Reference 39

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A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks 10 × 10nm 2 hf/hfo x crossbar resistive ram with excellent performance, reliability and low-energy operation,

Reference 40

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This paper cites Influence of oxygen vacancies in ald hfo2-x thin films on non-volatile resistive switching phenomena with a ti/hfo2-x/pt structure,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Influence of oxygen vacancies in ald hfo2-x thin films on non-volatile resistive switching phenomena with a ti/hfo2-x/pt structure,

Reference 41

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A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks A low-temperature-grown tio2-based device for the flexible stacked rram application,

Reference 42

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This paper cites Characterization and modeling of multilevel analog reram synapses in the sky130 process,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Characterization and modeling of multilevel analog reram synapses in the sky130 process,

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A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Neuromorphic Silicon Neuron Circuits,

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A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Mead, Analog VLSI and neural systems

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A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks A low-power adaptive integrate-and-fire neuron circuit,

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A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Hardware aware modeling of mixed-signal spiking neural network,

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This paper cites A quantitative description of membrane current and its application to conduction and excitation in nerve,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks A quantitative description of membrane current and its application to conduction and excitation in nerve,

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A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Hodgkin–Huxley Neuron and FPAA Dynamics,

Reference 49

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A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Backpropagation through time and the brain,

Reference 50

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A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Surrogate Gradient Learning in Spiking Neural Networks

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This paper cites Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccades,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccades,

Reference 52

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This paper cites A low power, fully event-based gesture recognition system,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks A low power, fully event-based gesture recognition system,

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This paper cites The heidelberg spiking data sets for the systematic evaluation of spiking neural networks,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks The heidelberg spiking data sets for the systematic evaluation of spiking neural networks,

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This paper cites Deep Learning for Event-based Vision: A Comprehensive Survey and Benchmarks.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Deep Learning for Event-based Vision: A Comprehensive Survey and Benchmarks

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A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Tonic: event-based datasets and transformations

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Observation 485f12cd-f5e5-4138-bc9e-9ecc5fb82142 · outbound

This paper cites Performance comparison of dvs data spatial downscaling methods using spiking neural networks,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Performance comparison of dvs data spatial downscaling methods using spiking neural networks,

Reference 57

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Observation 008824dd-d24e-47c2-9eba-8b07c35bb299 · outbound

This paper cites Sana-fe: Simulating advanced neuromorphic architectures for fast exploration,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Sana-fe: Simulating advanced neuromorphic architectures for fast exploration,

Reference 58

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Observation f8f8b53a-5c4f-4911-8a7b-e261edd219cf · outbound

This paper cites Open-source floating-gate cell for analogue synapses,.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Open-source floating-gate cell for analogue synapses,

Reference 59

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Observation 6d74ee39-b9fb-44b6-9669-ade7f5626689 · outbound

This paper cites Standard LIF neuron M84M1 M M3M2 C1 M5 M6 M9 M7 VspikeIleak Iin Figure S1: Standard LIF neuron circuit used in the manuscript The LIF neuron circuit, shown in Fig.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Standard LIF neuron M84M1 M M3M2 C1 M5 M6 M9 M7 VspikeIleak Iin Figure S1: Standard LIF neuron circuit used in the manuscript The LIF neuron circuit, shown in Fig

Reference 60

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Observation cadf7948-f1b4-439e-a704-63b0cceee674 · outbound

This paper cites an unresolved cited work.

A Hardware-Aware Open-Source Framework for Design Space Exploration of Mixed-Signal Spiking Neural Networks Unresolved cited work

Reference 61

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