In addressing the pattern synthesis of multi-constraint thinned planar antenna arrays, existing intelligent optimization algorithms encounter limitations such as premature convergence and insufficient solution accuracy. Therefore, we propose an adaptive mutation strategy dung beetle optimizer (AMSDBO) for optimizing thinned planar antenna arrays. The AMSDBO algorithm innovatively constructs a three-stage collaborative optimization framework, effectively achieving high-performance design for thinned planar arrays under the constraints of fixed aperture size and sparsity rate through a parameter adaptive adjustment mechanism. Firstly, initial solutions for the dung beetle populations are generated using a chaotic mapping reverse learning joint strategy to enhance both population diversity and the quality of the initial solutions. Next, an adaptive T-distribution mechanism is imposed to effectively enhance the early global search capability. Finally, the Lévy flight variation strategy is employed to adaptively adjust the positions of the dung beetle population in the later stages, helping the algorithm avoid local optima and accelerating convergence. Simulation results with classical test functions demonstrate that AMSDBO offers significant advantages in convergence accuracy and robustness compared to traditional algorithms (DBO, PSO and IWO). Additionally, two sets of typical planar thinned array experimental results indicate that the optimization performance of the AMSDBO algorithm is significantly improved compared to traditional optimization algorithms. Specifically, there is a peak sidelobe level (PSLL) reduction of 15.5% for DBO, 11.64% for PSO, and 14.56% for IWO. This confirms the effectiveness and superiority of the AMSDBO algorithm.

Gallium nitride (GaN) high electron mobility transistors (HEMTs) have attracted considerable attention due to high electron mobility, wide bandgap, and other advantageous properties. However, the self-heating that occurs at high power densities has emerged as a significant challenge that restricts HEMTs’ potential in high-performance applications. This study introduces a novel approach for extracting channel temperature distributions and thermal resistance, which considers the bias-dependence of the heat source model and the electro-thermal coupling among multiple gate fingers. The thermal resistance extracted by the optimized thermal model in this study differs from the traditional thermal model by 14.8% under a power density of 8W/mm and a base temperature of 1 0 0 ◦ C . The precision of the model is validated through infrared (IR) thermography, showing only a 1.76% discrepancy in the peak surface temperature of the filtered model compared to the measurement. To evaluate the model’s applicability across various conditions, comparisons are conducted between the model’s predictions and measurements across a range of ambient temperatures and power dissipation, revealing maximum errors of 4.1% at 7 5 ◦ C and 2.7% at 1 0 0 ◦ C . Finally, the influence of thermal boundary resistance (TBR) on the total thermal resistance is explored to provide guidance for device modeling and thermal management.

In order to address the challenges of complex process and low precision in traditional device modeling, based on the double hidden layer conjugate gradient back propagation neural network (CG-BPNN) and the double hidden layer Levenberg-Marquardt back propagation neural network (LM-BPNN), two small signal models are proposed and analyzed for the gallium arsenide (GaAs) pseudomorphic high electron mobility transistor (pHEMT) here. At first, the scattering parameters (S-parameters) of GaAs pHEMT are divided into training set and test set randomly. Experimental results show that the CG-BPNN is better than another S-parameters when predicting ImS12 with mean square error (MSE) of 1.0449e-05, while LM-BPNN predicts ImS12 with MSE of 3.0954e-06. Meanwhile, the MSE of CG-BPNN is higher than LM-BPNN when predicting all the S-parameters. In addition, it shows a smaller fluctuation range for the error curve of LM-BPNN, which is more stable than the CG-BPNN. Therefore, the double hidden layer LM-BPNN is the better choice to model the small signal of GaAs pHEMT.

A novel multi-conductor electromagnetic coupling model for the sensitive-wire subject to driven wire in a high-precision machining workbench is proposed in this paper. The general coupling model for an N-wire system is derived and is used to evaluate the wire coupling effect. Furthermore, 4-wire and 3-wire models are demonstrated to verify the accuracy through full-wave electromagnetic simulation below 10 MHz. The results show that the error between the proposed method and the full-wave electromagnetic simulation is less than 10%, demonstrating the high efficiency and accuracy of the proposed method. When the parameters of the driven power wire and the most sensitive wire are fixed and the parameters of neighboring wires are swept, the maximum fluctuation of the induced current on the most sensitive wire is 6.1 dB. The efficient calculation method proposed in this work helps reduce the risk of electromagnetic interference in complex electronic systems and improves the design efficiency of wires. It is promising to become a high-performance method with high efficiency and precision.

An algorithm is proposed to implement digital peeling to determine dominant time constants of an exponential transient process. The method is simpler to implement and reduces computational time to a large extent in comparison to other techniques widely used. Apart from a synthetic test function, the algorithm has been implemented on reported experimental transient decay curves of Cs 2HfCl 6 (CHC) single crystal scintillation to verify its efficacy. Finally, drain current detrapping transients of unpassivated AlGaN/GaN high electron mobility transistors (HEMTs) are analysed to determine the trap energy levels and concentrations. The validation of this digital peeling technique is also carried out by comparing with conventional method of time constant extraction from HEMT current transients. The extracted exponentials from the transient data efficiently fits well with the experimental data and can be extensively used for transient analysis. The digital peeling technique has wide applicability and can be used to analyze all exponential processes which occur in all domains of science.

This study presents a comparative analysis of radar cross section (RCS) simulations using Ansys High-Frequency Simulation Software (HFSS) and MATLAB. The primary objective is to evaluate the accuracy and consistency of RCS calculations performed by these two software tools for metallic cylinders. Metallic cylinders are selected as radar targets due to their well-defined and standardized shapes, which enable easier modeling and comparative analysis. To validate the RCS simulations, actual RCS measurements were conducted on an airport runway. The measurements took place at Kuala Lumpur International Airport (KLIA) using an FOD detection system operating at 93.1 GHz. By comparing the measured RCS data with the simulations results, the agreement and reliability of the simulation techniques were assessed, considering metallic cylinders of six different sizes. The findings indicate that the RCS values obtained from measurements align with the simulation results, exhibiting a similar RCS pattern. Both simulations exhibit minimal discrepancies, ranging between 0.01 to 0.1 dBsm. Through the analysis of the simulation results and measurements, valuable insight were gained regarding the performance and effectiveness of HFSS and MATLAB in predicting RCS values. Consequently, this study contributes to the understanding and validation of RCS simulation techniques and their practical applicability in real-world scenarios.

This paper, presents a 4×4 BM based on four direction switch BM antenna array. The proposed design operated at 3.5 GHz. The use of multi-beam antennas or switched-beam antenna arrays (SAAs) promised users of high-gain and large coverage areas for 5G technologies. The BM was implemented by combining 3-dB BLC, two crossovers, and 45 o phase shifters fabricated on the RT5880LZ substrate, with using a triangular slot and T-shape based on the BM design. The proposed design focused on the miniaturization and enhancement of the bandwidth. The return loss and isolation were better than -15 dB at all the ports, according to the simulated and measured result showed that with excellent insertion loss -6.1 ± 2 dB. A fractional bandwidth of 49.7% and the overall dimension were reduced to 56% as compared to the conventional BLC and crossover. Hence, the proposed design of BM performed an excellent size reduction of 80% and improvement bandwidth up to 836 MHz compared to the traditional BM. The switched beam directions were measured at -34 o, -40 o, +32 o and +35 o at 3.5 GHz for each input port of 1-4 excitation. The proposed design BM is suitable of 5G application.