Search Results (13)

We compare neural network architectures for aggregate loss triangle reserving under matched data, training, and evaluation protocols, separating architectural choice from hyperparameter configuration across hundreds of training runs. We compare the GRU Baseline of the DeepTriangle framework against two attention-augmented variants on Workers’ Compensation and Private Passenger Auto data from NAIC Schedule P, and we report two findings. First, attention does not improve reserving accuracy on these short triangles. Both attention variants exhibit a bimodal training instability we call “attention collapse”, in which a sizable fraction of seeds degenerate to a naive mean predictor and the remaining seeds do not reliably outperform the Baseline once the full seed distribution and post hoc survivor filters are considered. Adding or removing the padding mask changes the failure rate only modestly, indicating that the issue is not a masking bug but the limited cross-position information available in 9-lag aggregate triangles. Second, hyperparameter configuration is the dominant driver of accuracy: learning rate receives the largest share of impurity-based importance (about 46%) in a Random Forest decomposition, and tuning the GRU Baseline yields a larger gain over Chain–Ladder than any architectural variant tested. The tuned GRU Baseline remains the recommended starting point for aggregate triangle reserving. Full article

This paper presents a column-parallel adaptive-gain single-slope (SS) analog-to-digital converter (ADC) for high-speed high-dynamic-range (HDR) CMOS image sensors. Conventional adaptive-gain approaches often rely on dual-ramp generation or duplicated column circuits, which increase area and power overhead. In contrast, the proposed architecture achieves adaptive-gain operation using a single global ramp shared across all columns. A reconfigurable capacitive attenuation network embedded inside each column comparator locally scales the ramp at the comparator input, enabling seamless transition between high-gain operation for low-level signals and unity-gain operation for large signals within a single exposure and readout cycle. To suppress mode-dependent offsets while maintaining low noise, a configurable dual-source-follower ramp buffer symmetrically buffers the ramp and reference voltages during auto-zeroing and is reconfigured as a full-sized buffer during unity-gain conversion. Switching-induced column offsets are compensated using optical black pixels and lightweight digital processing. The ADC is implemented in a 110 nm CMOS image sensor process and validated through post-layout simulations including extracted parasitics and Monte Carlo mismatch analysis. The core ADC consumes 36.8 µW per column. Simulation results demonstrate linearity error below 1% without missing codes and show that the proposed AG_x8-to-AG_x1 configuration extends the effective dynamic range up to 78.3 dB. Full article

This paper proposes an iterative auto-tuning algorithm for PI controllers in permanent magnet synchronous motor (PMSM) drive systems. The controller gains are initially set using motor-parameter-based formulas derived from pole–zero cancelation, providing a theoretical first-order approximation. To address discrepancies caused by practical non-idealities such as delays, nonlinearities, and unmodeled dynamics, the proposed method iteratively refines the gains based on real-time measurements of time-domain performance indices. In each iteration, rise time, peak time, and percent overshoot are evaluated against predefined target values, and gain compensation terms are calculated accordingly. These compensations are applied to update the controller gains until all performance indices fall within the desired range, at which point the tuning process terminates automatically. The effectiveness of the proposed algorithm is validated through both MATLAB/Simulink simulations and real-time hardware experiments, demonstrating significant improvements in transient response, overshoot suppression, and closed-loop stability compared to conventional tuning approaches. Full article

The article presents an intelligent temperature transducer (ITT), which can work with a two-wire or a three-wire platinum resistance temperature detector (RTD). The ITT design allowed for compensation of the RTD’s lead wire resistance. The ITT used the author’s auto-calibration procedure, which minimized linearity errors of the ITT and RTD processing characteristics, ITT offset and gain errors, and errors resulting from changes in the ITT operating conditions concerning the nominal conditions. The presented results of a simulation and experimental studies confirmed the high effectiveness of this procedure. The determined uncertainty of temperature measurement using the Monte Carlo method and the obtained experimental results confirmed the possibility of measuring temperatures in the range of 0–200 °C with an expanded uncertainty of 0.02 °C at a 99% confidence level. Full article

Endoscopes are crucial for assisting in surgery and disease diagnosis, including the early detection of cancer. The effective use of endoscopes relies on their optical performance, which can be characterized with a series of metrics such as resolution, vital for revealing anatomical details. The modulation transfer function (MTF) is a key metric for evaluating endoscope resolution. However, the 2020 version of the ISO 8600-5 standard, while introducing an endoscope MTF measurement method, lacks empirical validation and excludes opto-electronic video endoscopes, the largest family of endoscopes. Measuring the MTF of video endoscopes requires tailored standards that address their unique characteristics. This paper aims to expand the scope of ISO 8600-5:2020 to include video endoscopes, by optimizing the MTF test method and addressing parameters affecting measurement accuracy. We studied the effects of intensity and uniformity of image luminance, chart modulation compensation, linearity of image digital values, auto gain control, image enhancement, image compression and the region of interest dimensions on images of slanted-edge test charts, and thus the MTF based on these images. By analyzing these effects, we provided recommendations for setting and controlling these factors to obtain accurate MTF curves. Our goal is to enhance the standard’s relevance and effectiveness for measuring the MTF of a broader range of endoscopic devices, with potential applications in the MTF measurement of other digital imaging devices. Full article

Heterodyne interferometry is playing an increasingly important role in the field of high-end equipment manufacturing. In photolithography, the precision requirement of displacement metrology is increasing to a deep sub-nanometer scale with the decrease in the critical dimension of chips. The error caused by light intensity changes was investigated, and its principle was found to be related to the time difference in photoelectric conversion. On the basis of the analysis of dynamic characteristics of interference light intensity changes in a heterodyne Michaelson interferometer, the influencing factors, and the features of the measurement error, equivalent measurement and real-time compensation methods were investigated and proposed. Experiments revealed that the error was 220 pm using the method of best-gain detection, while it was 4.8 nm using the method of auto-gain detection over a wide dynamic range when the light intensity was reduced by 30%. However, the proposed compensation method successfully reduced the error to less than 40 pm. Therefore, the real-time compensation method based on equivalent measurement can maintain the signal-to-noise ratio while improving the precision of photoelectric conversion, removing the error caused by intensity changes, and helping heterodyne interferometry achieve deep sub-nanometer precision. Full article

The success of robot localization based on visual odometry (VO) largely depends on the quality of the acquired images. In challenging light conditions, specialized auto-exposure (AE) algorithms that purposely select camera exposure time and gain to maximize the image information can therefore greatly improve localization performance. In this work, an AE algorithm is introduced which, unlike existing algorithms, fully leverages the camera’s photometric response function to accurately predict the optimal exposure of future frames. It also features feedback that compensates for prediction inaccuracies due to image saturation and explicitly balances motion blur and image noise effects. For validation, stereo cameras mounted on a custom-built motion table allow different AE algorithms to be benchmarked on the same repeated reference trajectory using the stereo implementation of ORB-SLAM3. Experimental evidence shows that (1) the gradient information metric appropriately serves as a proxy of indirect/feature-based VO performance; (2) the proposed prediction model based on simulated exposure changes is more accurate than using $\gamma$ transformations; and (3) the overall accuracy of the estimated trajectory achieved using the proposed algorithm equals or surpasses classic exposure control approaches. The source code of the algorithm and all datasets used in this work are shared openly with the robotics community. Full article

The fault tolerant control (FTC) technique is widely used in many industries to provide tolerance to systems so that they can operate when a system fault occurs. This paper presents a technique for FTC based on the observer signal application, which is used for a high-speed auto core adhesion mounting machine. The utilization of the observer signal information of the linear encoder fault is employed to adjust the gain parameters to achieve the appropriate gain value while maintaining the required performance of the system. The dynamic modeling of the servo motor system design utilizing a pole placement technique was designed to support the proposed method. A scaling gain fault step size adjustment from −1% to 1% with increments of 0.2% is used to simulate the fault conditions of the linear encoder. The statistical mean value of the observer error signal is used to train the artificial neural network (ANN) model. The results showed that the control system design successfully tracked the dynamic response. Furthermore, the ANN model, with more than 98% confidence, was satisfactory in classifying the linear encoder fault condition. The gain compensation was successful in reducing position error by more than 95% compared with the system without compensated gain. Full article

The inverse synthetic aperture radar (ISAR) imaging for targets with complex motions has always been a challenging task due to the time-varying Doppler parameter, especially at the low signal-to-noise ratio (SNR) condition. In this paper, an efficient ISAR imaging algorithm for maneuvering targets based on a noise-resistance bilinear coherent integration is developed without the parameter estimation. First, the received signals of the ISAR in a range bin are modelled as a multicomponent quadratic frequency-modulated (QFM) signal after the translational motion compensation. Second, a novel quasi-time-frequency representation noise-resistance bilinear Radon-cubic phase function (CPF)-Fourier transform (RCFT) is proposed, which is based on the coherent integration of the energy of auto-terms along the slope line trajectory. In doing so, the RCFT also effectively suppresses the cross-terms and spurious peaks interference at no expense of the time-frequency resolution loss. Third, the cross-range positions of target’s scatters in ISAR image are obtained via a simple maximization projection from the RCFT result to the Doppler centroid axis, and the final high-resolution ISAR image is thus produced by regrouping all the range-Doppler frequency centroids. Compared with the existing time-frequency analysis-based and parameter estimation-based ISAR imaging algorithms, the proposed method presents the following features: (1) Better cross-term interference suppression at no time-frequency resolution loss; (2) computationally efficient without estimating the parameters of each scatters; (3) higher signal processing gain because of 2-D coherent integration realization and its bilinear function feature. The simulation results are provided to demonstrate the performance of the proposed method. Full article

Radar coincidence imaging (RCI) is a high-resolution staring imaging technique without the limitation of relative motion between target and radar. The sparsity-driven approaches are commonly used in RCI, while the prior knowledge of imaging models needs to be known accurately. However, as one of the major model errors, the gain-phase error exists generally, and may cause inaccuracies of the model and defocus the image. In the present report, the sparse auto-calibration method is proposed to compensate the gain-phase error in RCI. The method can determine the gain-phase error as part of the imaging process. It uses an iterative algorithm, which cycles through steps of target reconstruction and gain-phase error estimation, where orthogonal matching pursuit (OMP) and Newton’s method are used, respectively. Simulation results show that the proposed method can improve the imaging quality significantly and estimate the gain-phase error accurately. Full article

We investigated the spectral and temporal characteristics of blue-violetfemtosecond optical pulses generated by a passively mode-locked GaInN laser diode ina dispersion-compensated external cavity. The output optical pulses at 400 nm wereanalyzed in detail by intensity auto- and cross-correlation measurements using secondharmonic generation on the surface of a β-BaB2O4 crystal. The obtained results clarifiedwavelength-dependent chirp characteristics of the optical pulses. The analysis suggestedthat a large frequency shift due to saturation in the saturable absorber and gain sectionsplayed an important role in the generation of femtosecond optical pulses. Full article

This manuscript describes a new type Ka-band airborne double-antenna microwave radiometer (ADAMR) designed for detecting atmospheric supercooled water content (SCWC). The source of the measurement error is investigated by analyzing the model of the system gain factor and the principle of the auto-gain compensative technique utilized in the radiometer. Then, a multipoint temperature correction method based on the two-point calibration method for this radiometer is proposed. The multipoint temperature correction method can eliminate the effect of changes in environmental temperature by establishing the relationship between the measurement error and the physical temperatures of the temperature-sensitive units. In order to demonstrate the feasibility of the correction method, the long-term outdoor temperature experiment is carried out. The multipoint temperature correction equations are obtained by using the least square regression method. The comparison results show that the measuring accuracy of the radiometer can be increased more effectively by using the multipoint temperature correction method. Full article

A single-chip sensor system-on-a-chip (SoC) that implements radio for 2.4 GHz, complete digital baseband physical layer (PHY), 10-bit sigma-delta analog-to-digital converter and dedicated sensor calibration hardware for industrial sensing systems has been proposed and integrated in a 0.18-μm CMOS technology. The transceiver’s building block includes a low-noise amplifier, mixer, channel filter, receiver signal-strength indicator, frequency synthesizer, voltage-controlled oscillator, and power amplifier. In addition, the digital building block consists of offset quadrature phase-shift keying (OQPSK) modulation, demodulation, carrier frequency offset compensation, auto-gain control, digital MAC function, sensor calibration hardware and embedded 8-bit microcontroller. The digital MAC function supports cyclic redundancy check (CRC), inter-symbol timing check, MAC frame control, and automatic retransmission. The embedded sensor signal processing block consists of calibration coefficient calculator, sensing data calibration mapper and sigma-delta analog-to-digital converter with digital decimation filter. The sensitivity of the overall receiver and the error vector magnitude (EVM) of the overall transmitter are −99 dBm and 18.14%, respectively. The proposed calibration scheme has a reduction of errors by about 45.4% compared with the improved progressive polynomial calibration (PPC) method and the maximum current consumption of the SoC is 16 mA. Full article