this paper presents a comparison study between the multilayer perceptron (mlp) and radial basis function (rbf) neural networks with supervised learning and back propagation algorithm to track hand gestures. both networks have two output classes which are hand and face. skin is detected by a regional based algorithm in the image, and then networks are applied on video sequences frame by frame in...

yarn tenacity is one of the most important properties in yarn production. this paper addresses modeling of yarn tenacity as well as optimally determining the amounts of the effective inputs to produce yarn with desired tenacity. the artificial neural network is used as a suitable structure for tenacity modeling of cotton yarn with 30 ne. as the first step for modeling, the empirical data is col...

the main purpose of this paper is prediction of tse corporate financial bankruptcy using artificial neural networks. the mean values of key ratios reported in past bankruptcy studies were selected for neural network inputs (working capital to total assets, net income to total assets, total debt to total assets, current assets to current liabilities, quick assets to current liabilities). the neu...

-Mimmtsatlon methods for trammgfeedforward networks with back propagatton are compared Feedforward neural network trammg ts a special case of functlon mmtmtsatton, where no exphctt model o f the data ts assumed Therefore, and due to the htgh dlmenstonahty o f the data, hneartsatton of the trainmg problem through use o f orthogonal basts functtons is not destrable The focus ts on functton mmlmts...

This paper is concerced with the use of error back-propagation in phonetic classification. Our objective is to investigate the basic characteristics of back-propagation, and study how the framework of multi-layer perceptrons can be exploited in phonetic recognition. We explore issues such as integration of heterogeneous sources of information, conditioll~ that can affect performance of phonetic...

The Non-Causal Decision-Feedback Equalizer (NCDFE) is a decision-aided equalizer that uses not only past decisions, like DFEs, but also future decisions, which usually come from another, classical equalizer. When there are no errors on the decisions, the NCDFE attains the Matched Filter bound (MFB). In practice, it suffers from the propagation of errors. We propose an implementation of the NCDF...

This review describes and motivates six principles for computational cognitive neuroscience models: biological realism, distributed representations, inhibitory competition, bidirectional activation propagation, error-driven task learning, and Hebbian model learning. Although these principles are supported by a number of cognitive, computational and biological motivations, the prototypical neura...

Output time prediction is a critical task to a wafer fab (fabrication plant). To further enhance the accuracy of wafer lot output time prediction, the concept of input classification is applied to Chen’s fuzzy back propagation network (FBPN) in this study by pre-classifying input examples with the self-organization map (SOM) classifier before they are fed into the FBPN. Examples belonging to di...

To further enhance the accuracy of lot output time prediction in a wafer fab (fabrication plant), a hybrid artificial neural network is proposed in this study. At first, the concept of input classification is applied to Chen’s fuzzy back propagation network (FBPN) by pre-classifying input examples with the self-organization map (SOM) classifier before they are fed into the FBPN. Then, examples ...