8 The training of some types of neural networks leads to separable non-linear least squares problems. These problems may be9 ill-conditioned and require special techniques. A robus...
The statistical pattern recognition based on Bayes formula implies the concept of mutually exclusive classes. This assumption is not applicable when we have to identify some non-ex...
In this paper we propose a Neural Net-PMRS hybrid for forecasting time-series data. The neural network model uses the traditional MLP architecture and backpropagation method of tr...
The objective in any pattern recognition problem is to capture the characteristics common to each class from feature vectors of the training data. While Gaussian mixture models ap...
Abstract. In this paper we give some pedagogical explanation of those situations where the use of redundant or almost-redundant information can improve the recognition rates of pat...