The conjugate gradient method with edge preserving regularization (CGEP) is applied to the ultrasound inverse scattering problem for the early detection of breast tumors. To accelerate image reconstruction, several different pattern classification schemes are introduced into the CGEP algorithm. These classification techniques are compared for a full-sized, two-dimensional breast model. One of t...

This paper presents a methodology for simulating urban growth phenomenon through utilizing remote sensing imagery and neural network (NN) algorithms. Historical satellite images of Indianapolis city, IN were used. All images were rectified and registered to Universal Transverse Mercator (UTM) NAD83 zone 16N. Supervised classification was used to classify the images to different land use categor...

Abstract. The Global Precipitation Measurement (GPM) mission measures global precipitation at a temporal resolution of few hours to enable close monitoring the hydrological cycle. GPM achieves this by combining observations from spaceborne radar, constellation passive microwave (PMW) sensors, and geostationary satellites. Goddard Profiling Algorithm (GPROF) is used operationally retrieve all PM...

In contrast to usually applied Neural Network (NN) based controllers where the structure and fixed parameters of NN were obtained off line, here we present a fully adaptive Internal Model-based Neural Control design aimed to unknown nonlinear industrial processes with stable dynamics. The internal model of the control plant is implemented by the NN provided with a Stochastic Gradient Descent (S...

This paper presents an automatic system for detection of breast cancer using data preprocessing and Bayesian network. In this study, ReliefF algorithm is used for reducing the dimension of breast cancer database then a pre-processing is done on the data and ultimately Bayesian network classifier is used for classification. The system performance has been compared with model NN (neural network) ...

The combination of acoustic models or features is a standard approach to exploit various knowledge sources. This paper investigates the concatenation of different bottleneck (BN) neural network (NN) outputs for tandem acoustic modeling. Thus, combination of NN features is performed via Gaussian mixture models (GMM). Complementarity between the NN feature representations is attained by using var...

OBJECTIVES The purpose of this research was to determine the mass concentrations of ions eluted from dental ceramic after an exposure to hydrochloric acid and, drawing on those results, to develop a feedforward backpropagation neural network (NN). MATERIALS AND METHODS Four dental ceramics were selected for this study. The experimental measurement was conducted after 1, 2, 3, 6 and 12 months ...

This article presents new neural network (NN) architecture to improve its ability for grade estimation. The main aim of this study is to use a specific NN which has a simpler architecture and consequently achieve a better solution. Most of the commonly used NNs have a fully established connection among their nodes, which necessitates a multivariable objective function to be optimized. Therefore...

INTRODUCTION: Hybrid stand-alone Small Wind Solar Energy System offers a feasible solution in remote areas where grid connectivity is either financially or physically unavailable. A small wind turbine (SWT) and solar photovoltaic system are part of the hybrid energy system, which effectively employed to meet needs rural household loads. OBJECTIVE: This research suggests an effective analysis co...