Multi layer perceptron with back propagation algorithm is popular and more used than other neural network types in various fields of investigation as a non-linear predictor. Though MLP can solve complex and non-linear problems, it cannot use missing data for training directly. We propose a training algorithm with incomplete pattern data using conventional MLP network. Focusing on the fact that ...

In this paper, we present a neural network architecture that belongs to the multi-layer perceptron family, associated with two different algorithms: the ordinary gradient and the natural gradient, we compare performances of those algorithms. The identification of a non-normalized power amplifier yielded to the introduction of an additional weight in the classical multilayer perceptron structure...

land cover map is important for many urban planning and management activities. in this study, in order to produce land cover map of arak city, digital image of liss-iii scanner acquired on 16 june 2006 were employed. first of all, geometric correction with rmse 0.58 pixel was applied. considering the mountainous condition of the study area, topographic correction was applied to the image. in su...

In this paper, we propose a deep neural network based natural language processing system for semantic textual similarity prediction. We leverage multi-layer bidirectional LSTM to learn sentence representation. After that, we construct matching features followed by Highway Multilayer Perceptron to make predictions. Experimental results demonstrate that this approach can’t get better results on s...

Speaker Recognition is a challenging task and is widely used in many speech aided applications. This study proposes a new Neural Network (NN) model for identifying the speaker, based on the acoustic features of a given speech sample extracted by applying wavelet transform on raw signals. Wrapper based feature selection applies dimensionality reduction by kernel PCA and ranking by Info gain. Onl...

In this paper, the application of neural networks to study the maximum and minimum relative humidity for Chandigarh city is explored. One important architecture of neural networks named Multi-Layer Perceptron (MLP) to model forecasting system is used and Back Propagation algorithm is used to train the network. The proposed network is trained with actual data of the past 10 years (2000-2010) and...

The aim of our study is to propose an approach for transfer function placental development using ultrasound images. This approach is based to the selection of tissues, feature extraction by discrete cosine transform DCT, discrete wavelet transform DWT and classification of different grades of placenta by artificial neural network and especially the multi layer perceptron MLP. The proposed appro...

Artificial neural network models have been studied for many years with the hope of designing information proeessing systems to produee human-like performance. The present artiele provides an introduction to neural computing by reviewing three commonly used models (namely, Hopfield's model, Kobonen's model and the Multi-layer perceptron) and showing their applications in various fields such as p...