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Wyniki wyszukiwania dla: surrogate modeling
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Patch size setup and performance/cost trade-offs in multi-objective antenna optimization using domain patching technique
PublikacjaA numerical study concerning multi-objective optimization of antenna structures using sequential domain patching (SDP) technique has been presented. We investigate the effect of various setups of the patch size on the operation of the SDP algorithm and possible trade-offs concerning the quality of the Pareto set found by SDP and the computational cost of the optimization process. Our considerations are illustrated using a UWB monopole...
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Fast geometry scaling of UWB band-notch antennas
PublikacjaImplementation of band-notch capability plays an important role in the design of ultra-wideband (UWB) antennas. At the same time, appropriate sizing of antenna geometry parameters in order to precisely allocate the notch at the required frequency as well as to ensure sufficient reflection level is quite challenging and has to be based—for reliability reasons—on full-wave electromagnetic (EM) simulations of the structure. In this...
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Rotational Design Space Reduction for Cost-Efficient Multi-Objective Antenna Optimization
PublikacjaCost-efficient multi-objective design of antenna structures is presented. Our approach is based on design space reduction algorithm using auxiliary single-objective optimization runs and coordinate system rotation. The initial set of Pareto-optimal solutions is obtained by optimizing a response surface approximation model established in the reduced space using coarse-discretization EM simulation data. The optimization engine is...
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Objective relaxation algorithm for reliable simulation-driven size reduction of antenna structure
PublikacjaThis letter investigates reliable size reduction of antennas through electromagnetic-driven optimization. It is demonstrated that conventional formulation of the design task by direct footprint miniaturization with imposing constraints on electrical performance parameters may not lead to optimum results. The reason is that—in a typical antenna structure—only a few geometry parameters explicitly determine the antenna footprint,...
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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublikacjaAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
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Rapid multi-criterial design of microwave components with robustness analysis by means of knowledge-based surrogates
PublikacjaManufacturing tolerances and uncertainties concerning material parameters, e.g., operating conditions or substrate permittivity are detrimental to characteristics of microwave components. The knowledge of relations between acceptable parameter deviations (not leading to violation of design specifications) and the nominal performance (not considering uncertainties), and is therefore indispensable. This paper proposes a multi-objective...
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Multi-objective design of miniaturized impedance transformers by domain segmentation
PublikacjaFast multi-objective design optimization of compact microstrip impedance transformers is discussed. Our approach exploits approximation models constructed using sampled coarse- mesh EM simulation data in a partitioned design space and response correction techniques for design refinement. Demonstra
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Comprehensive comparison of compact UWB antenna performance by means of multi-objective optimization
PublikacjaAn optimization-based procedure for comprehensive performance comparison of alternative compact UWB antenna topologies is discussed. The assessment of the antenna performance is conducted with respect to the structure size and its reflection response. More specifically, the best possible tradeoffs between these two figures of merit are identified through multiobjective optimization at the level...