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Modeling and computer-aided design (CAD) techniques are essential for microwave design, especially with the drive towards first-pass design success. We have described neural networks for microwave modeling and design. Neural networks are suitable when modeling a required relationship for which analytical formulas are hard to derive, or for which the computational effort is too high. This relationship...
This study presents the computer aided design (CAD) of type-I quantum-cascade lasers (QCLs) based on Artificial Neural Networks (ANNs). QCLs have critical quantities named modal gain, differential refractive index change and the linewidth enhancement factor (LEF, ?? parameter). Each of these quantities requires lengthy mathematical calculations using different theories and assumptions. The single...
Course scoring is the major criteria for measuring the teaching effect and a basis for improving the education quality. Analytic scoring of landscape CAD (computer-aided design) course is influenced by various factors. Relationships among these factors are complex, some are nonlinear, even some are random and fuzzy. It is difficult to explain their internal relationships with traditional method. This...
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 characteristics parameters of edge coupled coplanar waveguides (CPWs) have been determined with the use of models. These neural models were trained with LM, BR, QN,...
Neural network (NN) based CAD models have been developed for analysis and design of fin-lines. In the analysis phase, the network takes the dimensional parameters of the finline structure as its input and gives the characteristic impedance (Z0) and normalized guided wavelength (b/lambdacf) as its output. Another network, trained for design, takes Z0 along with other dimensions as input and produces...
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