Search Results (70)

This work presents a wideband variable gain low-noise amplifier (VGA-LNA) specifically engineered for medical systems operating in the C frequency band, which require the substantial amplification of low-intensity signals. The proposed design integrates a low-noise attenuator with a low-noise amplifier (LNA), fabricated using 90 nm CMOS technology and leveraging a combined common-source and common-gate topology. The integrated LNA achieved a notable power gain of 29 dB across a broad bandwidth of 2 GHz (6.4–8.4 GHz), maintaining an average noise figure (NF) below 3.14 dB. The design ensures superior impedance matching, demonstrated by reflection coefficients of S11 < −18.14 dB and S22 < −20.23 dB. Additionally, the amplifier exhibits a third-order input intercept point (IIP3) of 21.15 dBm while consuming only 83 mW from a 1.2 V supply voltage. A low-noise attenuator was incorporated at the input side to enable effective gain control through a digitally controlled variable gain, with step sizes ranging from 0.4 to 3.3 dB. This configuration enables a dynamic range of the transmission coefficient (|S₂₁|) from 16 dB to 23 dB, adjustable by 0.4 dB to 3.3 dB with a trade-off in an NF maintained at 6 dB. The VGA-LNA demonstrates exceptional potential for integration into wireless body area networks (WBANs), balancing flexible gain control with stringent performance metrics. Full article

Audio systems with unbalanced connections are susceptible to interference from ground loops, which manifests as hum and noise. This paper introduces and evaluates a novel passive Audio Interference Suppressor in Analog Audio Interface (AISAAI) designed to mitigate this problem. The AISAAI circuit is inserted between an audio device’s rectifier ground and its protective earth terminal, creating an optimized impedance path that reduces interference while ensuring safety. This approach is analyzed within a proposed Analog Audio Interconnection System (AAIS) framework. Experimental results show that common-mode voltages from protective earth potential differences are the primary source of interference. The optimized AISAAI suppressor achieves a consistent 15–30 dB reduction in measured audio interference across the audio band, regardless of the interconnect cable characteristics. This study confirms AISAAI as an effective solution for reducing ground loop noise in unbalanced audio systems and underlines the usefulness of the AAIS model for systemic analysis. Full article

Driven by the increasing global population and rapid urbanization, aircraft noise pollution has emerged as a significant environmental challenge, impeding the sustainable development of the aviation industry. Traditional noise prediction methods are limited by incomplete datasets, insufficient spatiotemporal consistency, and poor adaptability to complex meteorological conditions, making it difficult to achieve precise noise management. To address these limitations, this study proposes a novel noise prediction framework based on a hybrid Convolutional Neural Network–Bidirectional Long Short-Term Memory–Attention (CNN–BiLSTM–Attention) model. By integrating multi-source data, including meteorological parameters (e.g., temperature, humidity, wind speed) and aircraft trajectory data (e.g., altitude, longitude, latitude), the framework achieves high-precision prediction of aircraft noise. The Haversine formula and inverse distance weighting (IDW) interpolation are employed to effectively supplement missing data, while spatiotemporal alignment techniques ensure data consistency. The CNN–BiLSTM–Attention model leverages the spatial feature extraction capabilities of CNNs, the bidirectional temporal sequence processing capabilities of BiLSTMs, and the context-enhancing properties of the attention mechanism to capture the spatiotemporal characteristics of noise. The experimental results indicate that the model’s predicted mean value of 68.66 closely approximates the actual value of 68.16, with a minimal difference of 0.5 and a mean absolute error of 0.89%. Notably, the error remained below 2% in 91.4% of the prediction rounds. Furthermore, ablation studies revealed that the complete CNN–BiLSTM–AM model significantly outperformed single-structure models. The incorporation of the attention mechanism was found to markedly enhance both the accuracy and generalization capability of the model. These findings highlight the model’s robust performance and reliability in predicting aviation noise. This study provides a scientific basis for effective aviation noise management and offers an innovative solution for addressing noise prediction problems under data-scarce conditions. Full article

The optimal design of electromagnetic interference (EMI) filters relies on accurate characterization of noise source impedance. The conventional insertion loss method involves integrating two distinct passive two-port networks between the linear impedance stabilization network (LISN) and the equipment under test (EUT). The utilization of the insertion loss to formulate a system of binary quadratic equations concerning the real and imaginary components of the impedance of the noise source enables the precise extraction of the magnitude and phase of the noise source impedance in theory. However, inherent inaccuracies in the insertion loss method during extraction can compromise impedance accuracy or even cause extraction failure. This work employs a series inductance method to overcome these limitations. Exact analytical expressions are derived for the magnitude and phase of the noise source impedance. Subsequently, the application scope of the series insertion loss method is analyzed, and the impact of insertion loss measurement error on noise source impedance extraction accuracy is quantified. Requirements for improving extraction accuracy are discussed, and method optimization strategies are proposed. The permissible range of insertion loss error ensuring a solution exists is deduced. Finally, simulation and experimental results validate the proposed approach in a buck converter. Full article

XSPICE models for a generic transmission line, a microstrip line, and coupled microstrips are presented. The developed models extend general-purpose circuit simulation tools using RF circuits design features. The models could be used for circuit simulation in frequency, DC, and time domains for any active or passive RF or microwave schematic (including microwave monolithic integrated circuits—MMICs) involving transmission lines. The presented models could be used with any circuit simulation backend supporting XSPICE extensions and could be integrated without patching the core simulator code. The presented XSPICE models for microstrip lines take into account the frequency dependency of characteristic impedance and dispersion. The models were designed using open-source circuit simulation software. This study provides a practical example of the low-noise RF amplifier (LNA) design with Ngspice simulation backend using the proposed models. Full article

Accurately monitoring coupled water–nitrogen stress is critical for wheat (Triticum aestivum L.) productivity under climate change. This study developed a machine learning framework utilizing multimodal leaf electrophysiological signals––intrinsic resistance, impedance, capacitive reactance, inductive reactance, and capacitance––to decouple water and nitrogen stress signatures in wheat. A parallel modelling strategy was implemented employing Gradient Boosting, Random Forest, and Ridge Regression, selecting the optimal algorithm per feature based on predictive performance. Controlled pot experiments revealed IZ as the paramount biomarker across leaf positions, indicating its sensitivity to ion flux perturbations under abiotic stress. Crucially, algorithm-feature specificity was identified: Ridge Regression excelled in modeling linear responses due to its superior noise suppression, while GB effectively captured nonlinear dynamics. Flag leaves during reproductive stages provided significantly more stable predictions compared to vegetative third leaves, aligning with their physiological primacy as source organs. This framework offers a robust, non-invasive approach for real-time water and nitrogen stress diagnostics in precision agriculture. Full article

Noise reduction is essential in analyzing electrochemical impedance spectroscopy (EIS) data for accurate parameter identification of models of electrochemical sources and interfaces. EIS is widely used to study the behavior of electrochemical systems as it provides information about the processes occurring at electrode surfaces. However, measurement noise can severely compromise the accuracy of parameter identification and the interpretation of EIS data. This paper presents methods for parameter identification of Randles (also known as R-RC or 2R-1C) equivalent electrical circuits and noise reduction in EIS data using recursive filtering. EIS data obtained at the estimated characteristic frequency is processed with three equations in the closed form for the parameter estimation of series resistance, charge transfer resistance, and double-layer capacitance. The proposed recursive filter enhances estimation accuracy in the presence of random noise. Filtering is embedded in the estimation procedure, while the optimal value of the recursive filter weighting factor is self-tuned based on the proposed search method. The distinguished feature is that the proposed method can process EIS data and perform estimation with filtering without any input from the user. Synthetic datasets and experimentally obtained impedance data of lithium-ion batteries were successfully processed using PC-based and microcontroller-based systems. Full article

Challenges are brought to high impedance fault (HIF) line selection in traditional distribution networks by the fault signals with short windows and weak characteristics provided by new energy power sources. A new method driven by the symmetry of current traveling wave spectrum is proposed in this paper. Frequency-domain features are extracted by using Pisarenko spectral decomposition, and the differences in amplitude, frequency, and polarity between faulted and healthy feeders are analyzed. A similarity matrix is constructed with the help of Manhattan distance, and an improved density-based spatial clustering of application with noise (DBSCAN) clustering is adopted to achieve intelligent fault line selection. Experimental results show that compared with the steady state component method and the transient component method, the accuracy of this method is increased to 97.5%, with an improvement of more than 12.5%. Quantitative thresholds are replaced by qualitative spectrum differences, and this method is not affected by weak signals, thus solving the problem of threshold setting caused by the access of new energy. The accuracy of this method under different fault types, phases, and resistances is verified by simulation, ensuring easy engineering implementation. Full article

This paper presents a fully integrated bandpass filter (BPF) with high tunability based on a novel differential active inductor (DAI), designed for sensor interface circuits operating in the ultra-high frequency (UHF) band. The design of the proposed DAI is based on a symmetrical configuration, utilizing a differential amplifier for the feedforward transconductance and a common-source (CS) transistor for the feedback transconductance. By integrating a cascode scheme with a feedback resistor, the quality factor of the active inductor is significantly improved, leading to enhanced mid-band gain for the bandpass filter. To facilitate independent tuning of the BPF‘s center frequency and mid-band gain, an active resistor adjustment and bias voltage control are employed, providing precise control over the filter’s operational parameters. Post-layout simulations and process corner results are conducted with 0.13 µm CMOS technology at 1.2 V supply voltage. The proposed second order BPF achieves a broad tuning range of 280 MHz to 2.426 GHz, with a passband gain between 8.9 dB and 16.54 dB. The design demonstrates a maximum noise figure of 16.54 dB at 280 MHz, an input-referred 1 dB compression point of −3.78 dBm, and a third-order input intercept point (IIP3) of −0.897 dBm. Additionally, the BPF occupies an active area of only 68.2×30 µm², including impedance-matching part, and consumes a DC power of 14–20 mW. The compact size and low power consumption of the design make it highly suitable for integration into modern wireless sensor interfaces where performance and area efficiency are critical. Full article

This paper presents the design analysis of a low-power wideband single-ended CMOS low-noise amplifier (LNA). The proposed topology is based on a modified current- reuse circuit, in which two-stage common-source (CS) amplifiers consume the same DC current and are isolated from each other by large MIMCAPs, which results in good performance with low power consumption. The proposed circuit achieves a bandwidth of 2.5 GHz, suitable for several wireless communication standards such as GSM, WLAN, and Bluetooth. In the first stage, a current-reuse circuit with shunt feedback is used to satisfy input impedance matching and signal amplification with minimal noise injection. A common source (CS) with a source follower circuit forms the second stage to improve the noise figure (NF), harmonic distortion, and output impedance matching. The proposed LNA is designed in 65 nm CMOS technology and covers a frequency range of 0.17–2.68 GHz. The proposed LNA achieves a maximum gain of 17.24 dB, a minimum NF of 2.67 dB, a maximum IIP3 of −14.9 dBm, and input and output return losses of less than −10 dB. The power consumption of the proposed LNA is 3.52 mW from a 1 V power supply, and the core area is 0.3 mm². Full article

User-centered design (UCD) commonly requires direct player participation, yet budget limitations or restricted access to users can impede this goal. To address these challenges, this research explores a transformer-based approach coupled with a diffusion process to replicate real player behavior in a 2D side-scrolling action–adventure environment that emphasizes exploration. By collecting an extensive set of gameplay data from real participants in an open-source game, “A Robot Named Fight!”, this study gathered comprehensive state and input information for training. A transformer model was then adapted to generate button-press sequences from encoded game states, while the diffusion mechanism iteratively introduced and removed noise to refine its predictions. The results indicate a high degree of replication of the participant’s actions in contexts similar to the training data, as well as reasonable adaptation to previously unseen scenarios. Observational analysis further confirmed that the model mirrored essential aspects of the user’s style, including navigation strategies, the avoidance of unnecessary combat, and selective obstacle clearance. Despite hardware constraints and reliance on a single observer’s feedback, these findings suggest that a transformer–diffusion methodology can robustly approximate user behavior. This approach holds promise not only for automated playtesting and level design assistance in similar action–adventure games but also for broader domains where simulating user interaction can streamline iterative design and enhance player-centric outcomes. Full article

The feed-through effect of resonant pressure sensors usually introduces interfering noise signals, leading to the degradation of sensitivity, linearity, and other performances of the sensor test system. A low-noise charge amplifier and its feed-through compensation circuit are designed to realize high-precision measurements. The designed improved charge amplifier has a differential common-source structure as the output buffer stage, which can effectively reduce the output noise of the circuit while increasing the input impedance, thus improving the accuracy of the feed-through compensation coefficient. By establishing the equivalent circuit model of the sensor and analyzing the influence of the feed-through effect on the sensor test, the feed-through compensation circuit is designed to suppress the feed-through signal. Experimental testing of the sensor proves that the designed circuit can effectively suppress the feed-through effect of the sensor. The noise power spectral density of the improved charge amplifier is tested to be 26.74 nV/√Hz, which is a 65% reduction in noise density. The feed-through compensation circuit eliminates the interference frequency of 34,919 Hz introduced by the feed-through capacitor. Additionally, the resonance peak of the intrinsic resonance frequency of the pressure sensor is −40.75 dBV, which is reduced by 8 dBV compared with that before the feed-through compensation. The feed-through compensation circuit effectively reduces the feed-through interference signal of the sensor, improves the measurement accuracy of the test system, and provides technical support for the design of a low-noise, high-precision, stable, and reliable sensor test system. Full article

In complex underground parking scenarios, non-line-of-sight (NLOS) obstructions significantly impede positioning signals, presenting substantial challenges for accurate vehicle localization. While traditional positioning approaches primarily focus on mitigating NLOS effects to enhance accuracy, this research adopts an alternative perspective by leveraging NLOS propagation as valuable information, enabling precise positioning in NLOS-dominated environments. We introduce an innovative NLOS positioning framework based on the generalized source (GS) technique, which employs ray-tracing (RT) to transform NLOS paths into equivalent line-of-sight (LOS) paths. A novel GS filtering and weighting strategy to establish initial weights for the nonlinear equation system. To combat significant NLOS noise interference, a robust iterative reweighted least squares (W-IRLS) method synergizes initial weights with optimal position estimation. Integrating ultra-wideband (UWB) delay and angular measurements, four distinct localization modes based on W-IRLS are developed: angle-of-arrival (AOA), time-of-arrival (TOA), AOA/TOA hybrid, and AOA/time-difference-of-arrival (TDOA) hybrid. The comprehensive experimental and simulation results validate the exceptional effectiveness and robustness of the proposed NLOS positioning framework, demonstrating positioning accuracy up to 0.14 m in specific scenarios. This research not only advances the state of the art in NLOS positioning but also establishes a robust foundation for high-precision localization in challenging environments. Full article

In an investigation into how wind turbine noise interacts with the surrounding terrain, its propagation over rough ground is simulated using a parabolic equation code using a modified effective impedance model, which characterizes the effects of a three-dimensional, rigid roughness within a relatively long wavelength limit ($\mathrm{k}\mathrm{a}\le 1$). The model is validated by comparison to experiments conducted within an anechoic chamber wherein different source–receiver geometries are considered. The relative sound pressure level spectra from the parabolic equation code using the modified effective impedance model highlight a sensitivity to the roughness parameters. At a low frequency and far distance, the relative sound pressure level decreased as the roughness coverage increased. A difference of 4.9 dB has been reported. The simulations highlight how the roughness shifts the ground effect dips, resulting in the sound level at the distance of 2 km being altered. However, only the monochromatic wave has been discussed. Further work on broadband noise is desirable. Furthermore, due to the long wavelength limit, only a portion of audible wind turbine noise can be investigated. Full article

Fault location estimation in transmission lines is critical for power system reliability. Various methods have been developed for this purpose, among which transient frequency spectrum analysis (TFSA) stands out as a recent method based on travelling wave (TW) theory. TFSA determines the fault location by analyzing the frequency spectrum of transient currents and/or voltages at the instant of the fault, offering advantages such as independence from fault impedance and the ability to locate faults with one-side measurements. Despite its success in fault location, TFSA has several considerations that warrant detailed investigation. This study explores the effects of source inductance, series compensation, fault arc, and current transformer (CT) characteristics on transient frequencies. Additionally, the impact of noise on TFSA results is examined. The new proposed source inductance compensation method can reduce the error of 6.55% to 0.88%, where the same error can be reduced to 3.45% with the compensation method given in previous study. Strategies to enhance accuracy are discussed and compared to previous studies, including a proposed detection approach providing appropriate data size and precise wave propagation speed calculations. These findings contribute to a deeper understanding of TFSA’s limitations and inform practical improvements for fault location accuracy in power transmission systems. Full article