Linear Compensation Research Articles

Anatomical compensation of retinal nerve fiber layer improves the detection of glaucoma between ethnicities.

The study aimed to evaluate the impact of compensating retinal nerve fiber layer (RNFL) thickness for demographic and anatomical factors on glaucoma detection in Chinese and Indian adults. A population-based study included 1995 healthy participants (1076 Chinese and 919 Indians) to construct a multivariable linear regression compensation model. This model was applied to 357 Chinese glaucoma patients, 357 healthy Chinese, and 357 healthy Indians using Cirrus spectral-domain optical coherence tomography (OCT). The compensated RNFL thickness considered age, refractive error, optic disc parameters, and retinal vessel density. Results showed that although the average RNFL thickness was significantly higher in Chinese participants compared to Indians, the compensation model reduced this difference to nonsignificance. Moreover, the compensation model significantly improved the area under the receiver operating characteristic curve (0.90 vs. 0.78; p<0.001), sensitivity (75% vs. 51%), and specificity (67% vs. 32%) in distinguishing Chinese glaucoma patients from healthy Indian individuals. The compensation model significantly enhanced the diagnostic accuracy of RNFL thickness in distinguishing glaucoma in the Chinese ethnic group compared to the OCT instrument's default values. These results suggest that modifying RNFL measurements based on individual characteristics can yield substantial benefits for glaucoma detection across ethnicities.

Optimal Salesforce Compensation with General Demand and Operational Considerations

Problem definition: We investigate the optimal salesforce compensation scheme in the context of private information and unobservable actions, considering common operational factors encountered in practice, including inventory costs, contractible versus censored demand information, and controlled versus delegated ordering. Methodology/results: Based on an agency model with general demand and cost functions, we derive optimality conditions for implementable contracts that can achieve the second-best outcome in all scenarios. The contracts are in the forms of a menu with linear compensation for demand or sales, incorporating inventory costs. Moreover, the contracts feature adjustments in compensation corresponding to the ordering level if it is delegated. Managerial implications: Our study reveals that, under reasonably mild conditions, optimal salesforce contracts can still maintain relatively simple forms, even when confronted with common operational factors and generalized demand and cost functions. However, the contracts must be tailored to suit the operational settings. Intriguingly, neither the loss of demand information nor the delegation of inventory decisions would compromise system efficiency at optimum. Funding: H. Song is partially supported by the Key International Cooperation and Exchange Projects of the NSFC [Grant W2411062] and the Foundation for Innovative Research Groups of the NSFC [Grant 71821002]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0400 .

A linear compensation method for inference accuracy improvement of memristive in-memory computing

Memristive computing system (MCS), with the feature of in-memory computing capability, for artificial neural networks (ANNs) deployment showing low power and massive parallelism, is a promising alternative for traditional Von-Neumann architecture computing system. However, because of the various non-idealities of both peripheral circuits and memristor array, the performance of the practical MCS tends to be significantly reduced. In this work, a linear compensation method (LCM) is proposed for the performance improvement of MCS under the effect of non-idealities. By considering the effects of various non-ideal states in the MCS as a whole, the output error of the MCS under different conditions is investigated. Then, a mathematic model for the output error is established based on the experimental data. Furthermore, the MCS is researched at the physical circuit level as well, in order to analyze the specific way in which the non-idealities affect the output current. Finally, based on the established mathematical model, the LCM output current is compensated in real time to improve the system performance. The effectiveness of LCM is verified and showing outstanding performance in the residual neural network-34 network architecture, which is easily affected by the non-idealities in hardware. The proposed LCM can be naturally integrated into the operation processes of MCS, paving the way for optimizing the deployment on generic ANN hardware based on the memristor.

Learnable digital signal processing: a new benchmark of linearity compensation for optical fiber communications

The surge in interest regarding the next generation of optical fiber transmission has stimulated the development of digital signal processing (DSP) schemes that are highly cost-effective with both high performance and low complexity. As benchmarks for nonlinear compensation methods, however, traditional DSP designed with block-by-block modules for linear compensations, could exhibit residual linear effects after compensation, limiting the nonlinear compensation performance. Here we propose a high-efficient design thought for DSP based on the learnable perspectivity, called learnable DSP (LDSP). LDSP reuses the traditional DSP modules, regarding the whole DSP as a deep learning framework and optimizing the DSP parameters adaptively based on backpropagation algorithm from a global scale. This method not only establishes new standards in linear DSP performance but also serves as a critical benchmark for nonlinear DSP designs. In comparison to traditional DSP with hyperparameter optimization, a notable enhancement of approximately 1.21 dB in the Q factor for 400 Gb/s signal after 1600 km fiber transmission is experimentally demonstrated by combining LDSP and perturbation-based nonlinear compensation algorithm. Benefiting from the learnable model, LDSP can learn the best configuration adaptively with low complexity, reducing dependence on initial parameters. The proposed approach implements a symbol-rate DSP with a small bit error rate (BER) cost in exchange for a 48% complexity reduction compared to the conventional 2 samples/symbol processing. We believe that LDSP represents a new and highly efficient paradigm for DSP design, which is poised to attract considerable attention across various domains of optical communications.

Components of curvature-squared invariants of minimal supergravity in five dimensions

We present for the first time the component structure of the supersymmetric completions for all curvature-squared invariants of five-dimensional, off-shell (gauged) minimal supergravity, including all fermions. This is achieved by using an interplay between superspace and superconformal tensor calculus techniques, and by employing results from arXiv:1410.8682 and arXiv:2302.14295. Our analysis is based on using a standard Weyl multiplet of conformal supergravity coupled to a vector and a linear multiplet compensator to engineer off-shell Poincaré supergravity. We compute all the descendants of the composite linear multiplets that describe gauged supergravity together with the three independent four-derivative invariants. These are the building blocks of the locally superconformal invariant actions. A derivation of the primary equations of motion for minimal gauged off-shell supergravity deformed by an arbitrary combination of these three locally superconformal invariants, is then provided. Finally, all the covariant descendants in the multiplets of equations of motion are obtained by applying a series of Q-supersymmetry transformations, equivalent to successively applying superspace spinor derivatives to the primary equations of motion.

Frequency-adaptive odd-harmonic repetitive control scheme for three-phase shunt active power filters

Repetitive control (RC), which can track the periodic input or suppress the periodic disturbance with a zero steady-state error, is a promising control strategy for shunt active power filters (SAPF). However, the conventional RC (CRC) scheme will suffer a severe performance degradation caused by the grid frequency variations. In this article, a frequency-adaptive odd-harmonic repetitive control scheme with a single and fixed sampling rate is proposed for SAPF to deal with grid frequency variations and provide fast transient response for RC system. The frequency-adaptability of proposed repetitive control scheme can be implemented by updating the coefficients of the approximate expression for the delay unit in repetitive controller. The FIR filter based on Lagrange linear interpolation is used to transform the multirate repetitive control system into single-rate repetitive control system to address the problems caused by the multirate repetitive control system. Moreover, a fractional-order linear compensator with a simple structure is designed to compensate the magnitude and phase of the system accurately. Compared with other classical repetitive control strategies, the proposed repetitive control scheme can provide a better adaptation to the steady-state deviation and dynamic variation of grid frequency and ensure the control performance of SAPF system. Simulation and experimental results verify the effectiveness of the proposed control scheme.

Quantitative entropy-enthalpy compensation in intraprotein interactions from model compound data.

Many small globular proteins exist in only two states-the physiologically relevant folded state and an inactive unfolded state. The active state is stabilized by numerous weak attractive contacts, including hydrogen bonds, other polar interactions, and the hydrophobic effect. Knowledge of these interactions is key to understanding the fundamental equilibrium thermodynamics of protein folding and stability. We focus on one such interaction, that between amide and aromatic groups. We provide a statistically convincing case for quantitative, linear entropy-enthalpy compensation in forming aromatic-amide interactions using published model compound transfer-free energy data.

Origami-inspire quasi-zero stiffness structure for flexible low-frequency vibration isolation

As an emerging technology, origami exhibits rich nonlinear static and dynamic properties. However, simulating creases remains a key challenge hindering practice application, especially for volumetric (deformable) origami. Inspired by the bistable behavior and axial-rotational coupling mechanism of triangulated cylindrical origami (TCO), this paper proposes a novel combined truss-spring structure with additional inertial mechanism (TCTS-RIM) for low-frequency vibration isolation. Unlike pure TCO, the TCTS-RIM uses elastic linkages to simulate all creases and modifies crease positions, enhancing physical realization in engineering applications and offering tunable stiffness and inertia on demand. Static analysis shows the modified truss-spring structure in TCTS-RIM has superior quasi-linear negative stiffness compared to pure TCO, which enables a very wide quasi-zero stiffness (QZS) range via linear spring compensation. The wide QZS range for different loads can be realized by setting appropriate structural parameters. From system dynamic equations, nonlinear inertia, nonlinear quadratic force, and nonlinear damping due to RIM are identified and discussed. The Alternating frequency–time harmonic balance method is used to obtain the displacement transmissibility, and its parametric influencing investigations verify that the proposed TCTS-RIM has excellent low-frequency vibration isolation performance and rich tunability. Comparative discussions show the wide QZS range significantly reduces the resonance frequency, broadens the isolation frequency band, and yields superior dynamic performance versus pure TCO isolators. Moreover, equivalent mass, anti-resonance and softening behavior induced by the rotational inertia mechanism further enhance low-frequency vibration isolation performance. An experimental prototype is built, and experimental results validate the correctness of the theoretical analyses. This work presents a simple mechanical implementation of volumetric origami, which may progress the engineering applications of origami and provide a viable approach to low-frequency vibration control.

Robust practical prescribed time trajectory tracking of USV with guaranteed performance

In this paper, a practical prescribed time tracking control scheme is proposed to drive the unmanned surface vehicle (USV) under input saturation and unknown disturbances to track the desired trajectory with guaranteed transient and steady-state performances. First, by employing the logarithmic type barrier Lyapunov function and prescribed time function, the virtual velocity law is designed at the kinematic level. Then, to deal with the unknown disturbances, a prescribed time observer is constructed to achieve perturbation attenuation in a user-defined time. Together with the linear anti-windup compensator, a robust trajectory tracking controller is constructed, which is capable of guaranteeing that all signals in the closed-loop system are uniformly ultimately bounded (UUB) and the tracking error converges to a user-defined compact set in predetermined time with prescribed transient performance. Finally, the effectiveness of the proposed control scheme is validated through Lyapunov theory and numerical studies.

Adaptive linear neuron-based encoder measurement error compensation in vector control of two-phase stepping motors

Adaptive linear neuron-based encoder measurement error compensation in vector control of two-phase stepping motors

Linear and nonlinear stiffness compensation for low-frequency vibration isolation: a comparative study

Linear and nonlinear stiffness compensation for low-frequency vibration isolation: a comparative study

Develop an automated data acquisition system for TPS correction magnet power supply

Taiwan Photon Source is a third-generation 3 GeV synchrotron light source. Since the successful operation of the first beamline in 2013, comprehensive long-term testing and acceptance work has been carried out to ensure the stable operation of various types of correction magnet power supplies, totalling 1038 units. To standardise and save workforce and time for the measurement of correction magnet power supplies, an automated data acquisition system platform for correction magnet power supplies was developed using LabVIEW. This platform integrates control interface cards, high-resolution digital voltmeters, and analysis instruments. It also includes linearization and calibration compensation for the multi-channel direct constant current transformer to ensure simultaneous measurement of 24 magnet power supplies. Furthermore, it can automatically generate test reports in Word format, saving significant human resources and time. This platform has verified TPS correction magnet power supplies before installation, reducing the failure rate. Regarding measurement results, the output current ripple for the DCCT version is within five ppm, while the shunt resistor version is within ten ppm. The long-term current stability is consistently within ten ppm. The development of the fully automated data acquisition system platform and the measurement of 1038 power supplies were completed in four months.

Feedback linearization and equivalent-disturbance compensation control strategy for piezoelectric stage

Piezoelectric stages use piezoelectric actuators and flexure hinges as driving and amplifying mechanisms, respectively. These systems have high positioning accuracy and high-frequency responses, and they are widely used in various precision/ultra-precision positioning fields. However, the main challenge with these devices is the inherent hysteresis nonlinearity of piezoelectric actuators, which seriously affects the tracking accuracy of a piezoelectric stage. Inspired by this challenge, in this work, we developed a Hammerstein model to describe the hysteresis nonlinearity of a piezoelectric stage. In particular, in our proposed scheme, a feedback-linearization algorithm is used to eliminate the static hysteresis nonlinearity. In addition, a composite controller based on equivalent-disturbance compensation was designed to counteract model uncertainties and external disturbances. An analysis of the stability of a closed-loop system based on this feedback-linearization algorithm and composite controller was performed, and this was followed by extensive comparative experiments using a piezoelectric stage developed in the laboratory. The experimental results confirmed that the feedback-linearization algorithm and the composite controller offer improved linearization and trajectory-tracking performance.

DMCVS: Decomposed motion compensation‐based video stabilization

AbstractWith the popularity of handheld devices, video stabilization is becoming increasingly important. In previous studies, many methods have been proposed to stabilize shaky videos. However, these methods fail to balance between image content integrity and stability. Some methods sacrifice image content for better stability. Other methods ignore the subtle jitters, which leads to poor stability. This work innovatively proposes a video stabilization method based on decomposed motion compensation. First, a grid‐based motion statistics method is adopted for motion estimation, which obtains more accurate motion vectors according to matched likelihood estimates. Then, the motion compensation is inherently decomposed into two parts: linear motion compensation and auxiliary motion compensation. Linear motion compensation removes complex jitter by constructing linear path constraints to obtain a more stable camera path. Auxiliary motion compensation uses a moving average filter to remove the high‐frequency jitter as a supplement and preserve more image content. The two components are combined with individual weights to derive the final transform matrix and warp the original frames. Experimental results show that our method outperforms the previous methods on NUS and DeepStab datasets qualitatively and quantitatively.

Global Linearization Identification and Compensation of Nonresonant Dispersed Hysteresis for Piezoelectric Actuator

Global Linearization Identification and Compensation of Nonresonant Dispersed Hysteresis for Piezoelectric Actuator

Joint intra and inter-channel nonlinear compensation scheme based on improved learned digital back propagation for WDM systems.

In this paper, we improve the learned digital back propagation (LDBP) and propose a novel joint intra and inter-channel nonlinearity compensation scheme for polarization division multiplexing wavelength-division multiplexed (PDM-WDM) systems. From the perspective of interpretable neural network, the scheme realizes the alternating compensation of chromatic dispersion (CD) and nonlinearity based on physical models. The chromatic dispersion compensation (CDC) adopts one-dimensional convolution operation in the time domain. Moreover, the pulse-broadening effect is introduced into the overlap-and-save method. For nonlinear compensation, the improved joint model is applied, and the impact of the intra-channel pulse broadening and the walk-off effect between different channels caused by CD on the nonlinear effect is considered. To validate the effectiveness of the proposed scheme, we construct an 11-channel simulation system of 36 GBaud PDM uniform 16 quadrature amplitude modulation (PDM-16QAM) 1600 km and 64 GBaud PDM-64QAM 400 km, as well as a 5-channel experimental system of 28 GBaud PDM-16QAM 806.4 km. The simulation results show that the performance of PDM-16QAM with 0.5 steps per span and PDM-64QAM with 2 steps per span improve the Q-factor by approximately 0.75 dB and 0.54 dB at the optimal launch power, compared with the linear compensation scheme. The transmission performance of PDM-16QAM is higher than that of digital back propagation with 5 steps per span (DBP-5StPS), and the complexity is only 31.36% of that of DBP-5StPS. The performance of PDM-64QAM is higher than that of DBP-10StPS, with a complexity of 62.72%. The experimental results show that the performance of PDM-16QAM with 0.5 steps per span is improved with 0.86 dB Q-factor improvement compared with the linear compensation scheme at the optimal launch power, and the performance of the proposed scheme is higher than that of DBP-5StPS with a complexity of only 23.68%.

Experimentation and Application of Differential Inductive System for Machine and Human Body Parametric Measurement

In this article, the prototype circuit is constructed and tested to confirm the results obtained through simulation of a differential inductive circuitry. However, some number of errors found are reported in section 7. Analysis is done between the experimentally found results and those obtained from simulation. Test is done on all sections and certain test parameters are set to determine the actual performance of the system. The test parameters are the frequency response of the differential inductive circuit, the oscillatory effect of the movement of the core in and out of the coil, the inductance change, the force/pressure providing motion, wind pressure, the speed of the inward movement of the core and that of the outward movement, the number of turns used, the length of coils, the area of the coil topology, the diameter of the coil and that of the core, the mass of the convulsion bar, the mass of the target, the ambient temperature of the surrounding, density of the magnetic material used, the applied voltage to the timer, the resonant frequency reached, the amount of current voltage and frequency generated, the percentage of the duty cycle found on the resulting signal, the frequency hysteresis found, the range of oscillation bar, the height of coil arrangement, the seesaw concept, the output waveform of the signal, amongst others. The summary of the major contribution of this work includes a novel design of a differential inductive position sensory system along with its model in the form of the sensed parameter equations as a function of the displacement along the length of the coil. The analytical model for linearization compensation and improved transducer response is another component the author of this work claims it as contribution

A spectro-temporal modulation test for predicting speech reception in hearing-impaired listeners with hearing aids

Spectro-temporal modulation (STM) detection sensitivity has been shown to be associated with speech-in-noise reception in hearing-impaired (HI) individuals. Based on previous research, a recent study [Zaar, Simonsen, Dau, and Laugesen (2023). Hear Res 427:108650] introduced an STM test paradigm with audibility compensation, employing STM stimulus variants using noise and complex tones as carrier signals. The study demonstrated that the test was suitable for the target population of elderly individuals with moderate-to-severe hearing loss and showed promising predictions of speech-reception thresholds (SRTs) measured in a realistic set up with spatially distributed speech and noise maskers and linear audibility compensation. The present study further investigated the suggested STM test with respect to (i) test-retest variability for the most promising STM stimulus variants, (ii) its predictive power with respect to realistic speech-in-noise reception with non-linear hearing-aid amplification, (iii) its connection to effects of directionality and noise reduction (DIR+NR) hearing-aid processing, and (iv) its relation to DIR+NR preference. Thirty elderly HI participants were tested in a combined laboratory and field study, collecting STM thresholds with a complex-tone based and a noise-based STM stimulus design, SRTs with spatially distributed speech and noise maskers using hearing aids with non-linear amplification and two different levels of DIR+NR, as well as subjective reports and preference ratings obtained in two field periods with the two DIR+NR hearing-aid settings. The results indicate that the noise-carrier based STM test variant (i) showed optimal test-retest properties, (ii) yielded a highly significant correlation with SRTs (R2=0.61) exceeding and complementing the predictive power of the audiogram, (iii) yielded significant correlation (R2=0.51) with the DIR+NR-induced SRT benefit, and (iv) did not provide significant correlation with subjective preference for DIR+NR settings in the field. Overall, the suggested STM test represents a valuable tool for diagnosing speech-reception problems that remain when hearing-aid amplification has been provided and the resulting need for and benefit from DIR+NR hearing-aid processing.

A statistical characteristics preserving watermarking scheme for time series databases

Database watermarking is one of the most effective methods to protect the copyright of databases. However, traditional database watermarking has a potential drawback: watermark embedding will change the distribution of data, which may affect the use and analysis of databases. Considering that most analyses are based on the statistical characteristics of the target database, keeping the consistency of the statistical characteristics is the key to ensuring analyzability. Since statistical characteristics analysis is performed in groups, compared with traditional relational databases, time series databases (TSDBs) have obvious time-grouping characteristics and are more valuable for analysis. Therefore, this paper proposes a robust watermarking algorithm for time series databases, effectively ensuring the consistency of statistical characteristics. Based on the time-group characteristics of TSDBs, we propose a three-step watermarking method, which is based on linear regression, error compensation, and watermark verification, named RCV. According to the properties of the linear regression model and error compensation, the proposed watermark method generates a series of data that have the same statistical characteristics. Then, the verification mechanism is performed to validate the generated data until it conveys the target watermark message. Compared with the existing methods, our method achieves superior robustness and preserves constant statistical properties better.r.

A Voltage-Assist 16-Channel Electrochemical Biosensor with Linearity Compensation.

Large capacitive loading of electrodes induces massive error current and imperfect settling in the electrochemical signal acquisition process, leading to inaccurate acquisition results. To efficiently mitigate this inaccuracy, this paper presents a current-and-voltage dual-mode acquisition technique in which a voltage front-end (VFE) is employed to acquire the electrode voltage error and compensate the nonlinearity induced by the electrode capacitive loading. Therefore, the gain and bandwidth requirements of the current front end (CFE) can be relaxed to reduce the complexity and power consumption. With a relieved gain requirement, an inverter-based capacitive trans-impedance amplifier (IB-CTIA) is adopted to boost the input transconductance for low-noise design. By reusing the supply current, the IB-CTIA effectively achieves a low input-referred current noise of 3.9 pArms and a dynamic range (DR) of 126 dB with only 18-μW static power. The prototype chip is fabricated in a 180-nm CMOS process. Interleukin-6 immunoassays (IL-6) are implemented to verify the chip's performance. With the proposed nonlinear error compensation, the correlation coefficient of the detection result is improved from 0.951 to 0.980 and the limit of detection (LoD) is reduced from 8.31 pg/mL to 6.90 pg/mL.