Disclosed is a spiking neural network circuit, which includes an axon circuit that generates an input spike signal, a first synapse zone and a second synapse zone each including one or more synapses, wherein each of the synapses is configured to perform an operation based on the input spike ...
An initial neural circuit evolution space with rich basic components is essential. We define the set containing different receptive fields with different neuron types (excitatory, inhibitory) as neuronal clusters, as shown in Fig. 3. There are dense connections between the neuronal clusters in the ...
In: Advances in neural information processing systems, pp 1117–1125 Merolla PA, Arthur JV, Alvarez-Icaza R, Cassidy AS, Sawada J, Akopyan F, Jackson BL, Imam N, Guo C, Nakamura Y et al (2014) A million spiking-neuron integrated circuit with a scalable communication network and interface...
Neural Network Loss
The embodiment determines that the membrane potential value associated with the spiking neuron circuit reached a learning threshold value. The embodiment then performs a Spike Time Dependent Plasticity (STDP) learning function based on the determination that the membrane potential value of the spiking ...
CMOS Circuit Implementation of Spiking Neural Network for Pattern Recognition Using On-chip Unsupervised STDP Learning 鈥擟omputation on a large volume of data at high speed and low power requires energy-efcient computing architectures. Spiking neural network (SNN) with bio-inspired spike-timing- de...
We develop a VLSI implementation for the main gradient detector neurons, which could be integrated with standard comparator circuitry to develop a robust circuit for navigation and contour tracking.doi:10.48550/arXiv.1410.7883Shibani SanturkarBipin Rajendran...
fashion48, and individual neural circuits have clustered connectivity among excitatory neurons49,50. Such clustering could plausibly emerge due to synaptic plasticity, such as Hebbian learning51,52,53, and ‘soft winner-take-all’ networks are hypothesized to be a canonical cortical circuit54. ...
Similarly to a TTFS neuron model receiving information encoded in the timing (the exact spike arrival time) and computing a weighted sum of inputs spikes in its membrane potential which is then compared to a threshold39,40,41, a time-domain vector multiplication circuit receives information ...
The design of neural networks that are able to efficiently encode and detect conjunctions of features is an important open challenge that is also referred to as "the binding-problem". We define a formal framework for neural nodes that process activity in the form of tuples of spike-trains whi...