Surveys learning algorithms for recurrent neural networks with hidden units and puts the
various techniques into a common framework. The authors discuss fixed point learning …

Offline handwriting recognition is an image-based sequence recognition task within
computer vision. Traditional approaches rely on lexical segmentation, complex feature …

A new Chaotic Recurrent Neural Network (CRNN) is proposed to improve the learning
ability and the application to the speech recognition of Korean spoken digits and Korean …

Usually gradient descent is merely a way to find a minimum, abandoned if a more efficient
technique is available. Here we investigate the detailed properties of the gradient descent …

This paper proposes the use of a kind of acoustic units named stationary-transitional units
within a hybrid hidden Markov model/neural network recognition framework as an …

An intelligent judge neural network (IJNN) is developed to make decisions out of
contradictory arguments, which may come from different classifiers with different …

This paper describes hybrid Hidden Markov Models/Artificial Neural Networks (HMM/ANN)
models devoted to speech recognition, and in particular Loquendo HMM/ANN, that is the …

The integration of hidden Markov models (HMMs) and neural networks is an important
research line to obtain new speech recognition systems that combine a good time-alignment …

Many papers have addressed the problem of speeding up neural network execution, most of
them trying to reduce network size by weight and neuron pruning, and others making use of …

We proposed the novel single layer dynamic and static recurrent neural networks. These
networks can be used to the recognition of dynamic patterns. With the feedback connections …