Network-driven design principles for neuromorphic systems

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Network-driven design principles for neuromorphic systems

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2015 nî lūn-bûn

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2015年論文

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2015年論文

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Network-driven design principles for neuromorphic systems

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Network-driven design principles for neuromorphic systems

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Network-driven design principles for neuromorphic systems

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Network-driven design principles for neuromorphic systems

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Network-driven design principles for neuromorphic systems

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Network-driven design principles for neuromorphic systems

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P1476

Network-driven design principles for neuromorphic systems

@en

P2093

Johannes Partzsch

http://www.w3.org/2001/XMLSchema#string

Rene Schüffny

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P2860

Plasticity in memristive devices for spiking neural networks

On spike-timing-dependent-plasticity, memristive devices, and building a self-learning visual cortex.

A reconfigurable on-line learning spiking neuromorphic processor comprising 256 neurons and 128K synapses.

Finding a roadmap to achieve large neuromorphic hardware systems

Efficient physical embedding of topologically complex information processing networks in brains and computer circuits.

A comprehensive workflow for general-purpose neural modeling with highly configurable neuromorphic hardware systems.

The average distances in random graphs with given expected degrees.

Artificial brains. A million spiking-neuron integrated circuit with a scalable communication network and interface.

Characterization and compensation of network-level anomalies in mixed-signal neuromorphic modeling platforms.

Differential signaling via the same axon of neocortical pyramidal neurons.

P304

386

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P31

scholarly article

P356

10.3389/FNINS.2015.00386

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P478

http://www.w3.org/2001/XMLSchema#string

P577

2015-10-20T00:00:00Z

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P5875

283514061

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P698

26539079

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P932

4611986

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