Lead selenide PbSe thin films of different thicknesses (300, 500, and 700 nm) were deposited under vacuum using thermal evaporation method on glass substrates. X-ray diffraction measurements showed that increasing of thickness lead to well crystallize the prepared samples, such that the crystallite size increases while the dislocation density decreases with thickness increasing. A.C conductivity, dielectric constants, and loss tangent are studied as function to thickness, frequency (10kHz-10MHz) and temperatures (293K-493K). The conductivity measurements confirm confirmed that hopping is the mechanism responsible for the conduction process. Increasing of thickness decreases the thermal activation energy estimated from Arhinus equation is

The influence of silver doped n-type polycrystalline CdTe film with thickness of 200 nm and rate deposition of 0.3 nm.s -1 prepared under high vacuum using thermal co-evaporation technique on its some structural and electrical properties was reported. The X- ray analysis showed that all samples are polycrystalline and have the cubic zinc blend structure with preferential orientation in the [111] direction. Films doping with impurity percentages (2, 3, and 4) %Ag lead to a significant increase in the carrier concentration, so it is found to change from 23.493 108 cm -3 to 59.297 108 cm -3 for pure and doped CdTe thin films with 4%Ag respectively. But films doping with impurity percentages above lead to a significant decrease in the electrica

 Indium doped CdTe polycrystalline films of thickness equals to 300nm were grown on corning glass substrates at temperature equals to 423K by thermal co-evaporation technique. The structural and electrical properties for these films were studied as a function of heat treatment (323,373,423)K. The x-ray analysis showed that all samples are polycrystalline and have the cubic zincblende structure with preferential orientation in the [111] direction, no diffraction peaks corresponding to metallic Cd, Te or other compounds were observed. It was found that the electrical resistivity drops and the carrier concentration increases when the CdTe film doped with 1.5% indium and treated at different annealing temperatures.

     In this research, the electrical conductivity and Hall effect measurements have been investigated on the CuInTe2 (CIT) thin films prepared by thermal evaporation technique on glass substrate at room temperature as a function of annealing temperature (R.T,473,673)K for different thicknesses (300 and 600) nm. The samples were annealed for one hour.    The electrical conductivity analysis results demonstrated that all samples prepared have two types of transport mechanisms of free carriers with two values of activation energy (Ea1, Ea2), and the electrical conductivity increases with the increase of annealing temperature whereas it showed opposite trend with thickness , where the electrical conductivity would d

In this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two configuration serial-parallel model & parallel model to ensure that model output is equal to actual output of the system & to find the jacobain of the system. Which appears to be of critical importance parameter as it is used for the feedback controller and the second stage is learned on-line to modify the weights of the model in order to control the variable parameters that will occur to the system. A back propagation neural network is appl

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number