Add to ORKGIn the last decades many neuron models have been proposed in order to emulate the spiking behavior of the cortical neurons, from the simplest Integrateand- Fire to the most bio-realistic Hodgkin-Huxley model. The choice of which model have to be used depends on the trade-off between bio-plausibility and computational cost, that may be related to the specific purpose. The modeling of a continuous-time spiking neural network is the main purpose of this thesis. The “continuous-time” term refers to the fact that a spike can occur at any given time, thus in order to do exact computations without loss of information an exact ad hoc event-driven strategy for simulations has been implemented. In particular, the latter is suitable for the ...
In this work, a novel continuous-time spiking neural network paradigm is presented. Indeed, because...
In this work, a novel continuous-time spiking neural network paradigm is presented. Indeed, because...
The aim of this research is to develop a simple and effective continuous-time Spiking Neural Network...
In the last decades many neuron models have been proposed in order to emulate the spiking behavior ...
In the last decades many neuron models have been proposed in order to emulate the spiking behavior ...
In the last decades many neuron models have been proposed in order to emulate the spiking behavior ...
In the last decades many neuron models have been proposed in order to emulate the spiking behavior ...
In the last decades many neuron models have been proposed in order to emulate the spiking behavior ...
The aim of this research is to develop a simple and effective continuous-time Spiking Neural Network...
The aim of this research is to develop a simple and effective continuous-time Spiking Neural Network...
The aim of this research is to develop a simple and effective continuous-time Spiking Neural Network...
In this work, a novel continuous-time spiking neural network paradigm is presented. Indeed, because...
In this work, a novel continuous-time spiking neural network paradigm is presented. Indeed, because...
In this work, a novel continuous-time spiking neural network paradigm is presented. Indeed, because...
In this work, a novel continuous-time spiking neural network paradigm is presented. Indeed, because...
In this work, a novel continuous-time spiking neural network paradigm is presented. Indeed, because...
In this work, a novel continuous-time spiking neural network paradigm is presented. Indeed, because...
The aim of this research is to develop a simple and effective continuous-time Spiking Neural Network...
In the last decades many neuron models have been proposed in order to emulate the spiking behavior ...
In the last decades many neuron models have been proposed in order to emulate the spiking behavior ...
In the last decades many neuron models have been proposed in order to emulate the spiking behavior ...
In the last decades many neuron models have been proposed in order to emulate the spiking behavior ...
In the last decades many neuron models have been proposed in order to emulate the spiking behavior ...
The aim of this research is to develop a simple and effective continuous-time Spiking Neural Network...
The aim of this research is to develop a simple and effective continuous-time Spiking Neural Network...
The aim of this research is to develop a simple and effective continuous-time Spiking Neural Network...
In this work, a novel continuous-time spiking neural network paradigm is presented. Indeed, because...
In this work, a novel continuous-time spiking neural network paradigm is presented. Indeed, because...
In this work, a novel continuous-time spiking neural network paradigm is presented. Indeed, because...
In this work, a novel continuous-time spiking neural network paradigm is presented. Indeed, because...
In this work, a novel continuous-time spiking neural network paradigm is presented. Indeed, because...
In this work, a novel continuous-time spiking neural network paradigm is presented. Indeed, because...
The aim of this research is to develop a simple and effective continuous-time Spiking Neural Network...