background : the study examined the implementation of artificial neural network (ann) for the prediction of ammonia nitrogen removal from landfill leachate by ultrasonic process. methods : a three-layer backpropagation neural network was optimized to predict ammonia nitrogen removal from landfill leachate by ultrasonic process. considering the smallest mean square error (mse), the configuration...

In this paper we address the problem of rejecting Out-Of-Vocabulary words in speaker-independent Mandarin place name recognition. We integrate neural network and Hidden Markov Models in an attempt to utilize the strength of both. HMM based acoustic models including keyword models, filler models, and an anti-keyword model were trained to meet our needs. Statistical features are fed to a neural n...

This paper reports the study results on neural network training algorithm of numerical optimization techniques multiface detection in static images. The training algorithms involved are scale gradient conjugate backpropagation, conjugate gradient backpropagation with Polak-Riebre updates, conjugate gradient backpropagation with Fletcher-Reeves updates, one secant backpropagation and resilent ba...

Neural Network is a computational paradigm that comprises several disciplines such as mathematics, statistic, biology and philosophy. Neural Network has been implemented in many applications; in software and even hardware. In most cases, Neural Network considered large amount of data, as it will be teach to learn or memorize the data as the knowledge. The learning mechanism for Neural Network i...

The Architecture of BPNN’s A population P of objects that are similar but not identical allows P to be partitioned into a set of K groups, or classes, whereby the objects within the same class are more similar and the objects between classes are more dissimilar. The objects have N attributes (called properties or features) that can be measured (observed) so that each object can be represented b...