Optimization of a Microwave Amplifier Using Neural Performance Data Sheets with Genetic Algorithms

Güneş, Filiz; Cengiz, Yavuz

doi:10.1007/3-540-44989-2_75

Cited by 13 publications

(11 citation statements)

References 5 publications

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“…Here, only the plots of the sensitivities for the T and ⌸ types of amplifiers are presented, in comparison to each other. The design of these amplifiers was originally presented by Güneş and Cengiz in [10]. The design targets of the noise, input VSWR, and gain for both types of amplifiers were F req ϭ 0,46 dB (N 1, 12) and V ireq ϭ 1, G Treq ϭ 12 dB (N 15, 86), respectively, in the frequency range 2-11 GHz.…”

Section: Computed Resultsmentioning

confidence: 99%

Gain-sensitivity analysis for cascaded two-ports and application to distributed-parameter amplifiers

Güneş

Altunc

2004

Int J RF and Microwave Comp Aid Eng

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Section: Computed Resultsmentioning

confidence: 99%

Gain-sensitivity analysis for cascaded two-ports and application to distributed-parameter amplifiers

Güneş

Altunc

2004

Int J RF and Microwave Comp Aid Eng

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“…Optimization techniques facilitate enlarging the differential bandwidth Δ f of the equivalent circuit for a transistor to the whole operation bandwidth B at the chosen configuration type CT, bias condition V DS , I DS . Another alternative developed nowadays is the “Data‐basis” model which is the “Black‐Box Soft‐Model” resulted from application of the “Soft‐Computing” techniques [13–15]. In this article, the Black‐Box Soft‐Model for a microwave transistor is worked out using the neural network technique as the Soft‐Computing techniques [16].…”

Section: Amplifier Design Problemmentioning

confidence: 99%

Pareto‐optimal synthesis of microwave amplifier to design the noise‐constrained gain value

Cengiz

Konar

2012

Micro & Optical Tech Letters

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In this work, synthesis of microwave amplifier is put forward as a constrained vector optimization problem whose components are to meet the specific gain value constrained by the minimum noise over the available bandwidth. Nondominated solutions are acquired using the nondominated Sorting Genetic Algorithm‐II as a fast nondominated genetic sorting algorithm wherefore these synthesis objectives generally conflict with each other. Then, the Pareto frontiers are obtained using these trade‐off solution sets between the performance characterization of the device results in the triplet of gain GT, noise F, and input VSWR Vi and its source (ZS) and load (ZL). It can be concluded that the Pareto‐optimal synthesis procedure provides microwave amplifier with optimum performance. © 2012 Wiley Periodicals, Inc. Microwave Opt Technol Lett 54:1079–1084, 2012; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.26724

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“…In fact, authors have experienced many algorithms with gradients/heuristics approaches [9][10][11] in the circuit synthesis process; in this work, "Particle Swarm Optimization" (PSO) algorithm is employed as a simple and efficient by the derivative-free optimization tool in the syntheses process of the matching networks. In fact, nowadays evolutionary optimization algorithms have applied a wide range of electromagnetic problems, such as genetic optimization of the wideband multimodal square horns for discrete lenses [12] and diffusion coefficient of the turbulent jet [13] PSO design of the electromagnetic absorbers [14], PSO synthesis of the phased arrays [15], cylindrical conformal arrays [16] and smart antennas [17], null placement and side lobe reduction of the radiation patterns for the linear arrays using the ant colony optimization [18].…”

Section: Introductionmentioning

confidence: 99%

Design of an Ultra-Wideband, Low-Noise Amplifier Using a Single Transistor: A Typical Application Example

Demi̇rel¹,

Güneş²,

Ozkaya³

2009

PIER B

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Abstract-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 V i , Gain G T ) triplets and their (Z S , Z L ) terminations of a microwave transistor are exploited for the feasible design target space with the minimum noise F min (f ), maximum gain G T max (f ) and a low input VSWR V i over the available bandwidth B. This multi-objective design procedure is reduced into syntheses of the Darlington equivalences of the Z Sopt (f ), Z L max (f ) terminations with the Unit-elements and short-circuited stubs in the T -, L-, Π-configurations and Particle Swarm Intelligence is successfully implemented as a comparatively simple and efficient optimization tool into both verification of the design target space and the design process of the input and output matching circuits. A typical design example is given with its challenging performance in the simple Π-and Π-configurations realizable by the microstrip line technology. Furthermore the performances of the synthesized amplifiers are compared using an analysis programme in MATLAB code and a microwave system simulator and verified to agree with each other.

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Optimization of a Microwave Amplifier Using Neural Performance Data Sheets with Genetic Algorithms

Cited by 13 publications

References 5 publications

Gain-sensitivity analysis for cascaded two-ports and application to distributed-parameter amplifiers

Gain-sensitivity analysis for cascaded two-ports and application to distributed-parameter amplifiers

Pareto‐optimal synthesis of microwave amplifier to design the noise‐constrained gain value

Design of an Ultra-Wideband, Low-Noise Amplifier Using a Single Transistor: A Typical Application Example

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