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Minimal nonlinear dynamic neuron models of the generic bifurcation type may provide the middle way between the detailed models favored by experimentalists and the simplified threshold and rate model of computational neuroscientists. This thesis investigate ...
Spiking Neuron Networks (SNNs) are often referred to as the 3rd generation of neural networks. They derive their strength and interest from an accurate modelling of synaptic interactions between neurons, taking into account the time of spike emission. SNNs ...
Slow Feature Analysis (SFA) is an efficient algorithm for learning input-output functions that extract the most slowly varying features from a quickly varying signal. It has been successfully applied to the unsupervised learning of translation-, rotation-, ...
The use of large speech corpora in example-based approaches for speech recognition is mainly focused on increasing the number of examples. This strategy presents some difficulties because databases may not provide enough examples for some rare words. In th ...
Ultrasonic motors are a good alternative to electromagnetic motors in medical robotics, since they are electromagnetically compatible. Estimating speed instead of using encoders reduces cost and dimension of the robot on the one hand and increases reliabil ...
Since their introduction, Micro-Electrode Arrays (MEAs) have been exploited as devices providing distributed information about learning, memory and information processing in a cultured neuronal network, thus changing the field of view from single cell leve ...
The NEURON simulation environment has been extended to support parallel network simulations. Each processor integrates the equations for its subnet over an interval equal to the minimum (interprocessor) presynaptic spike generation to postsynaptic spike de ...
The use of large speech corpora in example-based approaches for speech recognition is mainly focused on increasing the number of examples. This strategy presents some difficulties because databases may not provide enough examples for some rare words. In th ...
We propose a novel network model of spiking neurons, without preimposed topology and driven by STDP (Spike-Time-Dependent Plasticity), a temporal Hebbian unsupervised learning mode, based on biological observations of synaptic plasticity. The model is furt ...
The goal of this work is to provide robust and accurate speech detection for automatic speech recognition (ASR) in meeting room settings. The solution is based on computing long-term modulation spectrum, and examining specific frequency range for dominant ...