<p>In our proposed structure, we injected a hidden layer to have a multilayer perceptron which<br> is more efficient than single layer perceptron.<br> To make this process clear, Figure 3 shows the neural networks for the HMM presented in<br> Figure 2.</p
with recognizing patterns, particularly visual and sound patterns. It is central to optical characte...
Beyond average firing rate, other measurable signals of neuronal activity are fundamental to an unde...
Abstract—Neurogenesis is that new neurons are gen-erated in the human brain. The new neurons create ...
<p>Based on the HMM structure in Figure 2, we can perform the following steps:<br> 1. Make the numbe...
<p>The chromosome which represents the HMM can be extracted from its corresponding neural<br> networ...
Hidden Markov Model (HMM) is a statistical model based on probabilities. HMM is becoming one of the ...
ABSTRACT Hidden Markov Model (HMM) is a statistical model based on probabilities. HMM is becoming o...
A general framework for hybrids of Hidden Markov models (HMMs) and neural networks (NNs) called Hidd...
IEEE Hidden Markov models (HMMs) underpin the solution to many problems in computational neuroscienc...
The author gives an algorithm to search the structure of a stochastic models with hidden variable. T...
This crossover is performed in the input layer part only. We choose a crossing cut point in the inpu...
A Layered Hidden Markov Model (LHMM) has been usually used for recognizing various human activities....
tput) is very commonly used to approximate unknown mappings. If the output layer is linear, such a n...
The performance of an Artificial Neural Network (ANN) strongly depends on its hidden layer architect...
Given recent experimental results suggesting that neural circuits may evolve through multiple firing...
with recognizing patterns, particularly visual and sound patterns. It is central to optical characte...
Beyond average firing rate, other measurable signals of neuronal activity are fundamental to an unde...
Abstract—Neurogenesis is that new neurons are gen-erated in the human brain. The new neurons create ...
<p>Based on the HMM structure in Figure 2, we can perform the following steps:<br> 1. Make the numbe...
<p>The chromosome which represents the HMM can be extracted from its corresponding neural<br> networ...
Hidden Markov Model (HMM) is a statistical model based on probabilities. HMM is becoming one of the ...
ABSTRACT Hidden Markov Model (HMM) is a statistical model based on probabilities. HMM is becoming o...
A general framework for hybrids of Hidden Markov models (HMMs) and neural networks (NNs) called Hidd...
IEEE Hidden Markov models (HMMs) underpin the solution to many problems in computational neuroscienc...
The author gives an algorithm to search the structure of a stochastic models with hidden variable. T...
This crossover is performed in the input layer part only. We choose a crossing cut point in the inpu...
A Layered Hidden Markov Model (LHMM) has been usually used for recognizing various human activities....
tput) is very commonly used to approximate unknown mappings. If the output layer is linear, such a n...
The performance of an Artificial Neural Network (ANN) strongly depends on its hidden layer architect...
Given recent experimental results suggesting that neural circuits may evolve through multiple firing...
with recognizing patterns, particularly visual and sound patterns. It is central to optical characte...
Beyond average firing rate, other measurable signals of neuronal activity are fundamental to an unde...
Abstract—Neurogenesis is that new neurons are gen-erated in the human brain. The new neurons create ...
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