International Journal of Numerical Modelling-Electronic Networks Devices and Fields最新文献

This article presents a model that can automatically produce a power amplifier's (PA) design parameters, that is, transmission lines (TLs) dimension, from a dataset of user-specified design goals like gain, efficiency, linearity, and scattering (S-) parameters. Based on the applied boundary conditions, a synthetic dataset is generated with the best range of design parameters (W and L). This dataset is utilized for training the physics-informed neural network (PINN) model with user-specified design goals as input and design parameters as target to produce the optimum value of W and L as the resultant output. Furthermore, utilizing the obtained dimensions, design, simulation, fabrication, and measurement of a PA are performed to validate our proposed model. The results of large signal measurements of PA are drain efficiency (DE) of 26.9%, power added efficiency (PAE) of 24.7%, output power (P_out) of 30.98 dBm at an input power $��\left(P_{\text{in}}\right)�$ of 19 dBm, and gain of 12.41 dB at an operating frequency of 1.625 GHz. It has been observed that the design parameters produced by the model have a significant agreement with the validated output. Also, the statistical error analysis is done by calculating the error metrics between the validated output and the actual output of the PA design.

In this paper, we propose a new method to approximate operators resulted from solving the scattering Problem in electromagnetism by dielectrically coated conducting bodies, using integral equations and high order impedance boundary condition. We introduce the variational Problem and we prove its well-posedness. After discretization, we find that operators arising from the high-order impedance boundary conditions are not well-defined. We present the new theoretical approach and highlight its potential through numerical experiments.

A miniaturized bandpass filter (BPF) with low insertion loss based on a modified T-section and a grounded transmission-zero resonator is proposed. The novel T-section consists of two resonators, which can achieve the bandpass performance with two transmission zeros (TZs) in the upper band. The grounded transmission-zero resonator can generate an extra transmission zero in the lower band. Therefore, high frequency selectivity can be achieved by the above three transmission zeros near the passband. The proposed BPF can achieve an insertion loss of 0.8 dB and a return loss of 22 dB covering 3.3–4.2 GHz, and the upper-stopband attenuation is better than 20 dB up to 12.5 GHz (3.3f₀). The proposed BPF with a miniaturized size of 1.2 mm × 0.5 mm × 0.3 mm have been fabricated using Si-based integrated passive devices (IPDs) technology and measured by on-wafer probing. The simulated and measured results of the proposed BPF are in reasonably good agreement.

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 Cs₂HfCl₆ (CHC) single crystal scintillation to verify its efficacy. Finally, drain current detrapping transients of unpassivated AlGaN/GaN high electron mobility transistors (HEMTs) are analyzed 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.

Deep learning-based methods for Low Probability of Intercept radar waveform recognition typically assume that the signal to be recognized belongs to a known and finite set of classes. However, in practical scenarios, the electromagnetic signal environment is open and there may be a large number of unknown signals, making such methods difficult to apply. To address this issue, a novel open-set recognition method based on reciprocal points is proposed. This approach uses a neural network to extract a high-dimensional time-frequency feature map of the signal, and measures the difference between the known and unknown signals by computing the distance between the feature vector and the reciprocal points. This allows the model to correctly identify known class signals while simultaneously detecting unknown signals. Experimental results show that the proposed method achieves open-set recognition of Low Probibability of Intercept radar signals. On test signals with signal-to-noise ratios ranging from 6 dB to 15 dB, the model achieves nearly 100% accuracy in identifying known class signals and more than 90% accuracy in detecting unknown signals.

The coupling of electromagnetic pulse (EMP) with the star-quad cable having reference conductor is analyzed by using the proposed model, which is based upon multi-conductor transmission line theory. Expressions for common-mode (CM) and differential-mode (DM) currents are developed. Two cases are mainly discussed: the first case is the star-quad cable with a central reference conductor, and the second case with the outside reference conductor. A rigorous comparison between these two cases shows that when the reference conductor is placed at the center, the magnitude of CM current is reduced dramatically, which is beneficial for electromagnetic compatibility (EMC). The CM current magnitude of the outside reference conductor is relatively very high due to the large CM current loop area, which is the least possible for the central reference conductor. There is no significant change in the DM current magnitude for both cases because the DM current has no direct dependence on the CM current loop area. A commercial software, FEKO, which utilizes the method of momentum (MoM), is used to compare the results of our proposed method, which are in good agreement.

The credible solution of discretized Maxwell's equations in spaces occupied by Lorentz dispersive media is the main subject of this work. Specifically, we introduce a finite-difference time-domain (FDTD) algorithm with a typical (2,4) structure that features dispersion-relation-preserving characteristics and produces reduced numerical errors in two-dimensional electromagnetic simulations, compared to the standard approach with similar computational requirements. We consider the case of dispersive media with non-vanishing absorption coefficients and investigate different options for the suitable modification of the spatial approximations, so that the accomplished accuracy is optimized for a given computational overhead. The properties of the proposed FDTD technique are thoroughly examined, both theoretically and in numerical tests, and the performance upgrade compared with the conventional solution is assessed.

A new temperature noise model, including the influence of gate-drain series resistance R_gd on the noise performance for an InP HEMT, is presented in this article. An equivalent temperature T_gd of R_gd has been taken into account based on Pospieszalski's noise model. The corresponding extraction procedure of noise parameters is given. Good correlation between the simulated and measured noise parameters in the frequency range of 8–50 GHz for a wide range of bias points verify the validity of the improved noise model.

Partial shading within arrays diminishes power output, induces hotspots, and compromises module integrity, thereby impacting system performance. The presence of bypass diodes further exacerbates these issues by introducing non-convexities in power curves, leading to additional power losses. To solve this problem, a new reconfiguration technique named Fibonacci Random Number Generator is proposed in this work which minimizes the effects of shading on the panels. The proposed methodology swiftly reduces current discrepancies between PV array rows by reshuffles the panels in an array to disperse the shade better using a mathematical formula resulting in increased power output and smoother power curves during partial shading events. The effectiveness of the proposed method is measured in terms of GMPP, row current calculations, power loss (PL), mismatch losses (ML), execution ratio (ER), fill factor (FF), and capacity factor (CF) for four distinctive shading conditions. Validation of results in software and hardware platforms showcase the applicability of proposed approach in real-time environments. Results indicate significant average power improvements of 25.49%, 15.47%, and 9.29% compared to existing popular reconfigurations like Skyscraper, Ken-Ken, and Chaotic baker map. The proposed method stands out as a potent tool for optimizing PV arrays within real-world systems grappling with partial shading issues.

An improved small-signal model applied to GaN-based devices is presented in this article. The extrinsic elements of the equivalent circuit topology are extracted using the test structures and the cut-off method. In order to obtain a good agreement between model simulations and measurements, distributed capacitive effects are taken into account. In addition, an inductance L_ds is introduced based on the conventional intrinsic equivalent circuit topology. Good agreement between the modeled and measured S-parameters is obtained for GaN HEMTs with a gate width of 2 × 100 μm (number of gate fingers × unit gate width) in the frequency range of 0.5–40 GHz.