The spiking neural network (SNN) is the third generation of artificial neural networks. The transmission and expression of information in SNN are performed by spike trains, making the SNN have the advantages of high calculation speed and low power consumption. Recently, researchers have employed the...
Fig. 1. Illustration of LIF neuronal model. The membrane potential accumulates over time, fires a spike when it reaches the threshold, and resets to resting potential. In order to facilitate the calculation and modelling, we convert the Eq. 1 into a discrete form as shown in Eq. 2, and ...
The network receives, in addition to the input x(t), a delayed target feedback signal \(y(t-\tau )\), and produces the output \({\hat{y}}(t)\) (where y(t) is the actual target). (B) Illustration of the two-link arm model with states given by the angle of the links, ...
Fig. 2. Illustration of the concept of Iterative Magnitude Pruning (IMP), Early-Bird (EB) ticket, and the proposed Early-Time (ET) ticket applied to EB ticket. Our ET ticket reduces search cost for winning tickets by using a smaller number of timesteps during the search process. Note, ...
(b) An illustration of SNNs trained with three different learning approaches, including synergistic learning between synaptic weights and spike thresholds and its two degenerate single-learning versions of synaptic learning and threshold learning. 图1:(a)时空反向传播示意图。在前馈路径中,每个脉冲神经元...
Fig. 5. Illustration of Divided Spatio-Temporal Attention scheme. We denote in white the query patch and show in orange its self-attention space–time neighborhood. Patches without color are not used for self-attention computation of the white patch. Note that δ is an arbitrary integer that ...
(a) Illustration of a biological neuron. A neuron receives pre-synaptic stimulus from dendrites, and synaptic integration occurs in soma. When a membrane voltage exceeds a threshold, a neuron generates an action potential, which is transmitted to other neurons through axon. (b,c) Neurotransmitter...
Equation (4) is an illustration of how complementary superposition information encoding works, with no factual significance. In this work, we focus on quantum image superposition encoding, as in Equation (5). However, it should be noted that any form of information that has a complement format,...
FIG. 1 is a block diagram depicting the components of a system for using a spiking neural network simulator for image processing according to the principles of the present invention; FIG. 2 is an illustration of a computer program product according to the principles of the present invention; FI...
A spiking neural network having a plurality layers partitioned into a plurality of frustums using a first partitioning may be implemented, where each frustum includes one tile of each partitioned layer of the spiking neural network. A first tile of a first layer of the spiking neural network ...