In this paper a wavelet transformation and artificial neural networks (ANN) approach is proposed for the image compression. The inputs to the network are the preprocessed data of original image, while the outputs are reconstructed image data, which are close to the inputs. By implementing the proposed scheme the influence of different compression ratios within the scheme is investigated. It has...

An adaptive neural network backstepping control for a class of uncertain nonlinear systems is presented in this paper. Three main issues will be treated: (1) unknown nonlinearities; (2) unknown system parameters; (3) external or internal disturbances. The proposed technique is applied to a simple pendulum. This latter is an unstable system which is perfectly described by a nonlinear model obtai...

Most Artificial neural networks (ANN) models used in the remote sensing classification are based on the multilayer perceptron (MLP) with back-propagation (BP) training algorithm. Compared to conventional statistical classifiers, MLP classifiers are non-parametric and distribution-free and is thus less restrictive in approximation, especially when distributions of features are strongly non-Gauss...

This paper presents a study on classification of blasts in acute leukemia blood samples using artificial neural network. In acute leukemia there are two major forms that are acute myelogenous leukemia (AML) and acute lymphocytic leukemia (ALL). Six morphological features have been extracted from acute leukemia blood images and used as neural network inputs for the classification. Hybrid Multila...

This paper designs a reconfigurable 5-fingers microstrip patch antenna using artificial neural networks (ANNs). The particular neural networks selected for this task are the source difference method (SD), multilayer perceptron (MLP), prior knowledge input method (PKI) and difference prior knowledge input method (PKID). Employing fine and coarse models for training the networks enables to develo...

In this paper, a new Transform Domain implementation of the well known Multilayer Perceptron Neural Network is presented. With the Transform Domain implementation, the input of the Neural Network can be represented in a more compact manner and the elements of the input vector become uncorrelated. The new Transform Domain Multilayer Perceptron (TDMLP) Neural Network is applied for the problem of...

In this work we present a variational formulation for a multilayer perceptron neural network. With this formulation any learning task for the neural network is defined in terms of finding a function that is an extremal for some functional. Thus the multilayer perceptron provides a direct method for solving general variational problems. The application of this numerical method is investigated th...

The Artificial Neural Network (ANN) Multilayer Perceptron (MLP) has shown good performance levels as discriminant system in text-independent Speaker Verification (SV) tasks, as shown in our work presented at Eurospeech 2001. In this paper, substantial improvements with regard to that reference architecture are described. Firstly, a new heuristic method for selecting the impostors in the ANN tra...

Prediction of Atmospheric Pressure is one important and challenging task that needs lot of attention and study for analyzing atmospheric conditions. Advent of digital computers and development of data driven artificial intelligence approaches like Artificial Neural Networks (ANN) have helped in numerical prediction of pressure. However, very few works have been done till now in this area. The p...

Artificial Neural Networks (ANN) performance depends on network topology, activation function, behaviors of data, suitable synapse's values and learning algorithms. Researchers used different learning algorithms to train ANN for getting high performance. Artificial Bee Colony (ABC) algorithm is one of the latest successfully Swarm Intelligence based technique for training Multilayer Perceptron ...