Neural network based equalizers can easily compensate channel impairments; such additive noise and inter symbol interference (ISI). The authors present a new approach to improve the training efficiency of the multilayer perceptron (MLP) based equalizer. Their improvement consists on modifying the back propagation (BP) algorithm, by adapting the activation function in addition to the other parameters of the MLP structure. The authors report on experiment results evaluating the performance of the proposed approach namely the back propagation with adaptive activation function (BPAAF) next to the BP algorithm. To further prove its effectiveness, the proposed approach is also compared beside a so known nonlinear equalizer explicitly the multilayer perceptron with decision feedback equalizer MLPDFE. The authors consider various performance measures specifically: signal resorted quality, lower steady state MSE reached and minimum bit error rate (BER) achieved, where nonlinear channel equalization problems are employed.

In recent years, the design and fabrication ofmulti-gate Metal Oxide Semiconductor Field Effect Transistors (MOSFETs) have attracted more efforts due to their high appropriateness for advanced integration circuits’ applications. In fact, the boost of MOSFET structures is a battle against parasitic phenomena appearing at the nanoscale level. Short channel and quantum confinement effects are among the critical drawbacks that need to be remedied carefully. On the other hand, the hot carrier degradation effect is mainly a reliability concern affecting the device per- formance after long duration of work. In response to the high computational costs related to the development of physi- cal based models for Double Gate (DG) MOSFETs including all these effects, more flexible alternatives have been proposed for the prediction of device performances. Our aim in this chapter is to investigate the efficiency of a new proposed frame- work, built upon Kriging metamodeling and Non-dominated Sorting Genetic Algorithm version II (NSGA II), for the optimal design in terms of OFF-current, threshold voltage and swing factor. The input variables of interest are limited to the geometrical parameters namely the channel length and thickness. Data generated according to computer experiments, based on ATLAS 2-D simulator, are used to identify and adjust Kriging surrogate models. It is emphasized that the obtained models can be used accurately in a multi-objective context to offer several Pareto optimal configurations. Therefore, a wide range of selection possibilities is avail- able to the designer depending on situations under consideration.

This paper proposes an artificial neural network (ANN) controller for the maximum power point tracking (MPPT) of a photovoltaic system under rapidly varying temperature and solar radiation conditions. This intelligent control method is applied to a DC/DC Buck-Boost converter. The main difference between the proposed systems to existing MPPT control systems is that it includes an automatic determination of the main switch duty cycle which permits an optimal operation of the control circuit under steady and perturbed environmental conditions. The maximum power point tracking controllers receive solar radiation and photovoltaic cell temperature as inputs, and it estimates the optimum duty cycle corresponding to maximum power as output. The different steps of the design of the intelligent controller are presented hereby with some simulation results using Matlab/Simulink software.

This paper proposes an artificial neural network (ANN) controller for the maximum power point tracking (MPPT) of a photovoltaic system under rapidly varying temperature and solar radiation conditions. This intelligent control method is applied to a DC/DC Buck-Boost converter. The main difference between the proposed systems to existing MPPT control systems is that it includes an automatic determination of the main switch duty cycle which permits an optimal operation of the control circuit under steady and perturbed environmental conditions. The maximum power point tracking controllers receive solar radiation and photovoltaic cell temperature as inputs, and it estimates the optimum duty cycle corresponding to maximum power as output. The different steps of the design of the intelligent controller are presented hereby with some simulation results using Matlab/Simulink software.

During the last years, in industrial process control, requirements for Continuous Emission Monitoring (CEM) have increased significantly. Most plants are investing in CEM systems in order to burn waste, obtain ISO 14000 and 18001 certification to protect operator's life. In this work, our approach describes development of a novel internet and fuzzy-based CEM system (IFCEMS). This system contains operator's stations for the bag filter's automation system and monitored using Internet. The object of the present installation consists of a suction ventilator, a bag filter and a system for collecting and evacuating the dust. To optimize the running of the bag filter workshop and ensure continuous control, the process based on one of the most powerful Artificial Intelligence techniques which is fuzzy logic involves the removal or filtration of smoke from the kiln and/or cement mill with control of temperature and pressure of the fumes.

In this paper, a new TiO2-based UV photodetector including back triangular texturization morphology has been investigated numerically using accurate solutions of Maxwell’s equations. A quantitative study of the device optical parameters like responsivity, sensitivity, detectivity, derived current capability and signal to noise ratio have been carried out in order to review the device overall optical performance for UV optical communication applications. Based on the obtained results, we have found that the device performance figures-of-merit (FoMs) governing the optical behavior is strongly improved as compared to its conventional planar counterpart, where the proposed design offers superior photocurrent, higher responsivity and sensitivity in comparison with those provided by the planar structure. These results led us to suggest the optimization of the proposed morphology using genetic algorithm (GA), in order to improve the electric field confinement and UV-light trapping in TiO2 absorber layer, where excellent ability has been recorded in enhancing the device absorbance. In this context, photodetector with optimized triangular texturization exhibits a 432% improvement, in term of responsivity, over planar structures and 120% improvement over the textured device without optimization. Thus, these encouraging results make the proposed device an extremely efficient candidate for high performance optoelectronic applications.

In this paper, we propose a new optically controlled field effect transistor, OC-FET, based on both surface texturization and graded gate doping engineering. The proposed design consists of a gate with both graded doping and surface texturization aspects to ensure high efficient light absorption and low dark current, respectively. Moreover, using an analytical investigation, an overall performance comparison of the proposed dual texturized gate (DTG) OC-FET device and conventional OC-FETs has been studied in order to confirm the enhanced optical and electrical performance of the proposed design in terms of increased photoresponsivity (R), optical gain (Formula presented.) ratio, drain current driving capability (Formula presented.) and high signal to noise ratio. Simulations show very good agreement between the results of the developed analytical models and those of TCAD software for wide range of design parameters. The developed analytical models are used to formulate the objective functions to optimize the device performance using a multi-objective genetic algorithm (MOGA). The proposed MOGA-based approach is used to search the optimal design parameters, for which the electrical and optical device performance is maximized. The obtained superior electrical performance suggests that our DTG OC-FET offers great promise as optical sensors and transducers for CMOS-based optical communications.