Salih Demirel

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In this work, a design method of an Ultra-Wideband (UWB), low-noise amplifier (LNA) is proposed exerting the performance limitations of a single high-quality discrete transistor. For this purpose, the compatible (Noise F , Input VSWR Vi, Gain GT ) triplets and their (ZS , ZL) terminations of a microwave transistor are exploited for the feasible design(More)
In this work, a novel multi-objective design optimization procedure is presented for the Minkowski Reflectarray RA s using a complete 3-D CST Microwave Studio MWSbased Multilayer Perceptron Neural Network MLP NN model including the substrate constant εr with a hybrid Genetic GA and Nelder-Mead NM algorithm. The MLP NN model provides an accurate and fast(More)
In this article, a power divider (PD) with dumb-bell shape defected ground structure (DGS) is investigated for miniaturization purpose. The proposed dumbbell shaped DGS are placed in the ground plane of a microstrip power divider. Firstly, a PD without DGS had been designed and simulated in Sonnet Suits environment to have the results for benchmarking.(More)
This paper presents the design optimization and analysis of Matching Circuits (MCs) composed of identical Composite Right/Left-Handed (CRLH) transmission cells in the balanced conditions. For this purpose, noise matching is considered as the Feasible Design Target (FDT) throughout the available bandwidth for a chosen low-noise microwave transistor which is(More)
In this work, an optimization of an Ultra-Wideband Low-Noise Amplifier (LNA) using a single symmetric Composite Right/Left-Handed Transmission Line (CRLH TL) cell in the balanced condition is presented by hybrid Genetic and Nelder-Mead Algorithm (GA-NMA). The GA-NMA multi-objective optimization is implemented independently to determine LC parameters for the(More)
Herein, a new methodology using a 3D Electromagnetic (EM) simulator-based Support Vector Regression Machine (SVRM) models of base elements is presented for band-pass filter (BPF) design. SVRM models of elements, which are as fast as analytical equations and as accurate as a 3D EM simulator, are employed in a simple and efficient Cuckoo Search Algorithm(More)
Honey Bee Mating Optimization (HBMO) is a recent swarm-based optimization algorithm to solve highly nonlinear problems, whose based approach combines the powers of simulated annealing, genetic algorithms, and an effective local search heuristic to search for the best possible solution to the problem under investigation within a reasonable computing time. In(More)
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