An attempt has been made to simulate the temperature distribution in prostate cancer tissue during laser ablation using finite element approach. Parameter studies have been carried out. The results have been consolidated using tool of artificial intelligence-Artificial Neural Network. Feed forward back propagation network has been used for this purpose. It has been found that artificial neural ...

Product unit neural networks with exponential weights (PUNNs) can provide more powerful internal representation capability than traditional feed-forward neural networks. In this paper, a convergence result of the back-propagation (BP) algorithm for training PUNNs is presented. The monotonicity of the error function in the training iteration process is also guaranteed. A numerical example is giv...

This paper investigates the potential of applying the feed forward neural network architecture for the classification of breast cancer. Back-propagation algorithm is used for training multi-layer artificial neural network. Missing values are replaced with median method before the construction of the network. This paper presents the results of a comparison among ten different hidden neuron initi...

A phonetic classification scheme based on a feed forward recurrent back-propagation neural network working on audio and visual information is described. The speech signal is processed by an auditory model producing spectral-like parameters, while the visual signal is processed by a specialised hardware, called ELITE, computing lip and jaw kinematics parameters. Some results will be given for va...

Modularity and hierarchy are fundamental notions in structured system design. By subdividing a large and unstructured problem into smaller and tractable chunks, design automation becomes possible. In this paper we discuss the use of modularity and hierarchy for functional specialization during the development of neural networks. We study the behavioral differences and requirements for back-prop...

This paper presents a segmental durations’ model applied to the European Portuguese language for TTS purposes. The model is based on a feed-forward neural network, trained with a back-propagation algorithm, and has as input a set of phonological and contextual features, automatically extracted from the text. The relative importance of each feature, concerning the correlation with segmental dura...

We propose a general class of multilayer feed-forward neural networks where the combination of inputs in every node is formed by hybrid linear and nonlinear (of the morphological/rank type) operations. For its design we formulate a methodology using ideas from the back-propagation algorithm and robust techniques to circumvent the non-diierentiability of rank functions. Experimental results in a...