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We apply multilayer perceptron (MLP) based hierarchical Tandem features to large vocabulary continuous speech recognition in Mandarin. Hierarchical Tandem features are estimated using a cascade of two MLP classifiers which are trained independently. The fi ...
The distribution of synaptic efficacies in neocortex has an approximately lognormal shape. Many weak synaptic connections coexist with few very strong connections such that only 20% of synapses contribute 50% of total synaptic strength. Furthermore, recent ...
Using phone posterior probabilities has been increasingly explored for improving automatic speech recognition (ASR) systems. In this paper, we propose two approaches for hierarchically enhancing these phone posteriors, by integrating long acoustic context, ...
Sequences of events in noise-driven excitable systems with slow variables often show serial correlations among their intervals of events. Here, we employ a master equation for generalized non-renewal processes to calculate the interval and count statistics ...
We analyze a simple hierarchical architecture consisting of two multilayer perceptron (MLP) classifiers in tandem to estimate the phonetic class conditional probabilities. In this hierarchical setup, the first MLP classifier is trained using standard acous ...
Multiple types of measures have been developed to measure the similarity between two spike trains. These were extensively used to classify neuron responses according to stimuli and to validate mathematical models that predict the spike times. Here we analy ...
Statistical models of neural activity are at the core of the field of modern computational neuroscience. The activity of single neurons has been modeled to successfully explain dependencies of neural dynamics to its own spiking history, to external stimuli ...
We analyze the class of networks characterized by modular structure where a sequence of l Erdos-Renyi random networks of size N >> 1 with random average degrees is joined by links whose structure must remain immaterial. We find that traceroutes spanning th ...
The ability of simple mathematical models to predict the activity of single neurons is important for computational neuroscience. In neurons, stimulated by a time-dependent current or conductance, we want to predict precisely the timing of spikes and the su ...
In this thesis, we investigate a hierarchical approach for estimating the phonetic class-conditional probabilities using a multilayer perceptron (MLP) neural network. The architecture consists of two MLP classifiers in cascade. The first MLP is trained in ...
