PARALLEL-HIERARCHICAL NETWORK LEARNING METHODS AND THEIR APPLICATION TO PATTERN RECOGNITION L. I. Timchenko, a† V. V. Melnikov, a‡ and N. I. Kokryatskaya b UDC 658.012:681.32:621.38 Abstract. This paper considers provisions necessary for developing parallel-hierarchical network learning methods underlain by the idea of population coding in an artificial neural network and its approximation to n...

Sign language is the communication process of people with hearing impairments. For hearing-impaired in Bangladesh and parts India, Bangla sign (BSL) standard. While one most widely spoken languages world, there a scarcity research field BSL recognition. The few works done so far focused on detecting alphabets. To best our knowledge, no work words has been conducted till now for unavailability w...

in this study, artificial neural network was used to predict the surface tension of 20 hydrocarbon mixtures. experimental data was divided into two parts (70% for training and 30% for testing). optimal configuration of the network was obtained with minimization of prediction error on testing data. the accuracy of our proposed model was compared with four well-known empirical equations. the arti...

natural fire inflicting irreparable damage to rangelands and forest areas is cause changes in landscape ecology. the purpose of this research is comparison of artificial neural network (ann) and line regression (lr) models to predict of forest and rangelands fires to this end, the data consist fire burned area and fire were used weather data over a period of 7 years (2006-2012(.the result indic...

water quality assessment provides a scientific basis for water resources development and management. this case study proposes a factor analysis- hopfield neural network model (fhnn) based on factor analysis method and hopfield neural network method. the results showed that the factor analysis (fa) technique was introduced to identify important water quality parameters. results revealed that bio...