Abstract   Background : Leukemia is one of the mostcommon cancers in children, comprising more than a third of all   childhood cancers. Newly affected patients in USA are estimated as 10100cases, and if these cases are diagnosed late or proper treatment is not applied, then it can be mortal. Because rapid and proper diagnosis of leukemia based on clinical or medicinal findings (without biopsy...

In this paper, an Artificial Neural Networks (ANN) model has been developed to design the multilayer Rectangular microstrip patch. In the design procedure, synthesis ANN model is used as feed forward network to calculate the resonant frequency. Analysis ANN model is used as the reverse side of the problem to calculate the antenna dimension. The network is trained with the data obtained from mea...

Artificial neural networks (ANNs) have been promising tools for many applications. In recent years, a computer-aided design approach based on (ANNs) has been introduced to microwave modelling, simulation and optimization. In this work, the characteristic parameters of top shielded multilayered coplanar waveguides (CPWs) have been determined with the use of ANN models. These neural models were t...

The aim of this paper is to propose a new Kalman Filter Recurrent Neural Network (KFRNN) topology and a recursive Levenberg-Marquardt (L-M) algorithm of its learning capable to estimate states and parameters of a highly nonlinear Continuous Stirred Tank Bioreactor (CSTR) in noisy environment. The estimated parameters and states obtained by the proposed KFRNN identifier are used to design an ind...

For managing data in a smart card’s limited memory, containing medical and biometric images, images compression is resorted to. For image retrieval, it is necessary that the classification algorithm be efficient to search and locate the image in a compressed domain. This study proposes a novel training algorithm for Multi-Layer Perceptron Neural Network (MLP-NN) to classify compressed images. M...

In the last decades, Italian road transport system has been characterized by severe and consistent traffic congestion in particular Rome is one of cities most affected this problem. study, a Levenberg-Marquardt (LM) artificial neural network heuristic model was used to predict flow non-autonomous vehicles. Traffic datasets were collected using both inductive loop detectors video cameras as acqu...

This paper presents two innovative evolutionary-neural systems based on feed-forward and recurrent neural networks used for quantitative analysis. These systems have been applied for approximation of phenol concentration. Their performance was compared against the conventional methods of artificial intelligence (artificial neural networks, fuzzy logic and genetic algorithms). The proposed syste...

This paper describes the efficient MPPT tracking for variable wind speed using an artificial neural network. The network has been trained backpropagation algorithm and Levenberg-Marquardt (LM) based optimization technique to achieve maximum power point. A multilevel inverter having 10 switches used reduce voltage stress, THD switching losses resulting in improvement performance reduction driver...

In our previous work we proposed some extensions of the Levenberg-Marquardt algorithm; the Bacterial Memetic Algorithm and the Bacterial Memetic Algorithm with Modified Operator Execution Order for fuzzy rule base extraction from inputoutput data. Furthermore, we have investigated fuzzy flip-flop based feedforward neural networks. In this paper we introduce the adaptation of the Bacterial Memet...

In this paper, we propose the block-diagonal matrix to approximate the Hessian matrix in the Levenberg Mar-quardt method in the training of neural networks. Two weight updating strategies, namely asynchronous and synchronous updating methods were investigated. Asyn-chronous method updates weights of one block at a time while synchronous method updates all weights at the same time. Variations of...