spiking neuron
Identification of linear and nonlinear sensory processing circuits from spiking neuron data
... the spiking neuron parameters or the filter structure, and do not assume that the input of the neuron ...the spiking neuron and the identification of the ...
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Computing with spiking neuron networks a review
... Spiking Neuron Networks (SNNs) are often referred to as the third generation of neural ...“spiking neuron”, summarizes the most currently-in-use models of neurons and synaptic plasticity, the ...
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A Spiking Neuron Based Feature Model for Real Time Object Recognition
... using spiking neuron based supervised learning ...the spiking neuron model is presented by the ...firing neuron concept to perform activity analysis and ...a spiking ...
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Analog Spiking Neuron with Charge-Coupled Synapses
... a spiking signal, the second MOS capacitor is driven into the deep depletion state, and the weight charge is released to the output terminal due to the lat- eral potential ...the spiking cur- rent is ...
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Spiking neuron models of the medial and lateral superior olive for sound localisation
... For this work single spike encoding is used where the single sound source was assigned arbitrarily chosen values of t1 and t2 to represent the signal delay at each ear, as a function of angle (see Fig. 4). Each output ...
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Nonsmooth dynamics in spiking neuron models
... of spiking neural networks are a key part of modern approaches to understanding the dynamics of biological neural ...of spiking neurons with a reduction in the dimensionality of both parameter and variable ...
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Investigation of a Chaotic Spiking Neuron Model
... Figure 3 shows just one example of the stabilised orbits, however there are very large number of stabilised orbits for different period lengths τ . To demonstrate this, an experimentation has been set up to calculate the ...
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Spiking Neural Network on Curve Fitting
... The spiking neuron is a mathematical model that is closer to the biological ...Sigmoid neuron model changes a real number input into a real number output signal by passing a transfer ...the ...
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Simplified spiking neural network architecture and STDP learning algorithm applied to image classification
... Different spiking neuron mathematical models exist, but their computational complexity makes them ill-suited for hardware ...(SRM) neuron with spike-time dependent plasticity (STDP) learning is ...
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Vol 5, No 07 (2017)
... i.e., Spiking Neuron Model, Multiplicative Neuron Model and Multilayer Perceptron Model have been taken for ...that spiking neuron model can be considered the best model in context of ...
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FPGA Based Platform for Spiking Neural Network
... the neuron scientific realism and computational ...in spiking neurons. In this view, a neuron include its incoming synapses acts mathematically as filter or operator in that it maps incoming sets of ...
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Temporal Information Processing and Stability Analysis of the MHSN Neuron Model in DDF
... real neuron on a chip [9, ...hybrid spiking neuron models are suitable choice for chip level implementation due to their simple mathematical treatment [3, 9, 13, ...These neuron models are ...
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Computational geometry for modeling neural populations: From visualization to simulation
... point spiking neuron models that defines the state of the population in terms of a density function over the neural state ...dimensional neuron models to 2D ones as they offer a rich dynamical ...
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Effect of the Neuron Coding by Gaussian Receptive Fields on Enhancing the Performance of Spiking Neural Network for an Automatic Lipreading System
... SNN approach for an automatic Lipreading An automatic lipreading method is generally integrated as visual feature to support a speech recognition system and enhance their performance. In our work, we exclusively used ...
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A CMOS based Neuron Circuit for Spiking Neural Networks with Memristive Synapse
... brained-inspired spiking neural networks (SNNs), which can be applied on visual information processing and speech recognition, is attracting great attention especially when combined with emerging electronic ...
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A Rate-Reduced Neuron Model for Complex Spiking Behavior
... a spiking neuron (Rulkov [14], Rulkov et ...complex spiking behavior into existing neural field ...the spiking neuron network (and vice versa), this greatly simplifies the otherwise ...
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A compact spike-timing-dependent-plasticity circuit for floating gate weight implementation
... post-pre spiking event, no update of the synaptic weight ...pre-post spiking event will however cause the synaptic weight, which is represented as charge on the FG of the synapse, to be ...
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Characterization of a descending pathway: activation and effects on motor patterns in the brachyuran crustacean stomatogastric nervous system
... IV neuron somata. Furthermore, in those species where the IV neuron somata are located in the ivn root rather than in the brain, rhythmic activity was present even in the absence of the ...IV neuron ...
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Neurons of self-defence: neuronal innervation of the exocrine defence glands in stick insects
... Different sensory inputs and pathways activate the se- cretion from defence glands, especially upon direct con- tact via mechanosensory stimuli as well as visual stimuli ([15, 19, 21, 28–32] for Anisomorpha buprestoides ...
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Influence of application techniques on the ecotoxicological effects of nanomaterials in soil
... dry spiking methods. Wet spiking resulted in stronger effects than dry ...dry spiking were concentration-dependent for the selected test concentra- tions (3-6 concentrations, depending on the test) ...
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