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Journal articles on the topic 'Electrochemical measurement; Adaptive algorithms'

Author: Grafiati

Published: 4 June 2021

Last updated: 15 February 2022

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1

González, Francisco, David Greiner, Vicente Mena, Ricardo M. Souto, Juan J. Santana, and Juan J. Aznárez. "Fitting procedure based on Differential Evolution to evaluate impedance parameters of metal–coating systems." Engineering Computations 36, no. 9 (2019): 2960–82. http://dx.doi.org/10.1108/ec-11-2018-0513.

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Purpose Impedance data obtained by electrochemical impedance spectroscopy (EIS) are fitted to a relevant electrical equivalent circuit to evaluate parameters directly related to the resistance and the durability of metal–coating systems. The purpose of this study is to present a novel and more efficient computational strategy for the modelling of EIS measurements using the Differential Evolution paradigm. Design/methodology/approach An alternative method to non-linear regression algorithms for the analysis of measured data in terms of equivalent circuit parameters is provided by evolutionary a

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Alhasa, Kemal, Mohd Mohd Nadzir, Popoola Olalekan, et al. "Calibration Model of a Low-Cost Air Quality Sensor Using an Adaptive Neuro-Fuzzy Inference System." Sensors 18, no. 12 (2018): 4380. http://dx.doi.org/10.3390/s18124380.

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Conventional air quality monitoring systems, such as gas analysers, are commonly used in many developed and developing countries to monitor air quality. However, these techniques have high costs associated with both installation and maintenance. One possible solution to complement these techniques is the application of low-cost air quality sensors (LAQSs), which have the potential to give higher spatial and temporal data of gas pollutants with high precision and accuracy. In this paper, we present DiracSense, a custom-made LAQS that monitors the gas pollutants ozone (O3), nitrogen dioxide (NO2

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Miñambres, J. J., and M. de la Sen. "Fast Adaptive Control Algorithms in pH Measurement." IFAC Proceedings Volumes 19, no. 15 (1986): 313–16. http://dx.doi.org/10.1016/s1474-6670(17)59440-9.

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Kübler, Jonas M., Andrew Arrasmith, Lukasz Cincio, and Patrick J. Coles. "An Adaptive Optimizer for Measurement-Frugal Variational Algorithms." Quantum 4 (May 11, 2020): 263. http://dx.doi.org/10.22331/q-2020-05-11-263.

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Variational hybrid quantum-classical algorithms (VHQCAs) have the potential to be useful in the era of near-term quantum computing. However, recently there has been concern regarding the number of measurements needed for convergence of VHQCAs. Here, we address this concern by investigating the classical optimizer in VHQCAs. We introduce a novel optimizer called individual Coupled Adaptive Number of Shots (iCANS). This adaptive optimizer frugally selects the number of measurements (i.e., number of shots) both for a given iteration and for a given partial derivative in a stochastic gradient desc

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Crompvoets, Elise A. V., Anton A. Béguin, and Klaas Sijtsma. "Adaptive Pairwise Comparison for Educational Measurement." Journal of Educational and Behavioral Statistics 45, no. 3 (2019): 316–38. http://dx.doi.org/10.3102/1076998619890589.

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Pairwise comparison is becoming increasingly popular as a holistic measurement method in education. Unfortunately, many comparisons are required for reliable measurement. To reduce the number of required comparisons, we developed an adaptive selection algorithm (ASA) that selects the most informative comparisons while taking the uncertainty of the object parameters into account. The results of the simulation study showed that, given the number of comparisons, the ASA resulted in smaller standard errors of object parameter estimates than a random selection algorithm that served as a benchmark.

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Yang, Haiyan, Hongqiang Liu, Zhongliang Zhou, and An Xu. "A practical adaptive nonlinear tracking algorithm with range rate measurement." International Journal of Distributed Sensor Networks 14, no. 5 (2018): 155014771877686. http://dx.doi.org/10.1177/1550147718776863.

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It is difficult to answer the problem whether the range rate measurement should be adopted to track a target in a tracking scenario. A practical adaptive nonlinear tracking algorithm with the range rate measurement is proposed, which avoids this problem and achieves good accuracy of target state estimation. First, three popular nonlinear filtering algorithms only with the position measurement are surveyed. Second, three popular nonlinear filtering algorithms with the position and range rate measurements are surveyed. Then, a novel tracking algorithm with range rate measurement is proposed base

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Roscoe, A. J., I. F. Abdulhadi, and G. M. Burt. "P and M Class Phasor Measurement Unit Algorithms Using Adaptive Cascaded Filters." IEEE Transactions on Power Delivery 28, no. 3 (2013): 1447–59. http://dx.doi.org/10.1109/tpwrd.2013.2238256.

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Münch, K., W. Vilser, and I. Senff. "Adaptive Algorithmen zur automatischen Messung retinaler Gefäßdurchmesser - Adaptive Algorithms for the Automatic Measurement of Retinal Vessel Diameters." Biomedizinische Technik/Biomedical Engineering 40, no. 11 (1995): 322–25. http://dx.doi.org/10.1515/bmte.1995.40.11.322.

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Alekseev, V. V., E. M. Antonyuk, and I. E. Varshavskiy. "Algorithmic Support of Adaptive Automatic Control Systems with Data Compression." Journal of the Russian Universities. Radioelectronics 23, no. 6 (2020): 84–99. http://dx.doi.org/10.32603/1993-8985-2020-23-6-84-99.

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Introduction. The exponential growth of measurement information caused by ongoing complication of technical and production facilities necessitates the development of improved or brand new information and measurement systems, including those performing adaptive automatic control functions. Automatic criteria-based selection and reduction of measurement information continuously supplied by multi-parameter sources characterizing the objects under study require algorithms ensuring reconfiguration of automatic control systems during operation. In comparison with automatic control systems based on t

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Chabaud, Ulysse, Damian Markham, and Adel Sohbi. "Quantum machine learning with adaptive linear optics." Quantum 5 (July 5, 2021): 496. http://dx.doi.org/10.22331/q-2021-07-05-496.

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We study supervised learning algorithms in which a quantum device is used to perform a computational subroutine – either for prediction via probability estimation, or to compute a kernel via estimation of quantum states overlap. We design implementations of these quantum subroutines using Boson Sampling architectures in linear optics, supplemented by adaptive measurements. We then challenge these quantum algorithms by deriving classical simulation algorithms for the tasks of output probability estimation and overlap estimation. We obtain different classical simulability regimes for these two c

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Danilova, S. K., and N. N. Tarasov. "Adaptive Algorithm of Filtration with Integrated Residuals." Mekhatronika, Avtomatizatsiya, Upravlenie 20, no. 2 (2019): 80–89. http://dx.doi.org/10.17587/mau.20.80-89.

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This paper proposes a filtering algorithm based on the use of not only the residuals between the measured and estimated coordinates, as in classical filtering algorithms, but also multiple integrals of these residuals. Classical filtering algorithms use reliable information about both the motion and measurement models and the statistical characteristics of the input random disturbances and measurement noise. The real control objects operate under conditions of action not only of highfrequency random disturbances, but also under the influence of low-frequency forces and moments from an aggressi

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Russo, Daniel. "Simple Bayesian Algorithms for Best-Arm Identification." Operations Research 68, no. 6 (2020): 1625–47. http://dx.doi.org/10.1287/opre.2019.1911.

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This paper considers the optimal adaptive allocation of measurement effort for identifying the best among a finite set of options or designs. An experimenter sequentially chooses designs to measure and observes noisy signals of their quality with the goal of confidently identifying the best design after a small number of measurements. Just as the multiarmed bandit problem crystallizes the tradeoff between exploration and exploitation, this “pure exploration” variant crystallizes the challenge of rapidly gathering information before committing to a final decision. The paper proposes several sim

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Zigic, Aleksandar. "Experimental verification of preset time count rate meters based on adaptive digital signal processing algorithms." Nuclear Technology and Radiation Protection 20, no. 2 (2005): 40–44. http://dx.doi.org/10.2298/ntrp0502040z.

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Experimental verifications of two optimized adaptive digital signal processing algorithms implemented in two pre set time count rate meters were per formed ac cording to appropriate standards. The random pulse generator realized using a personal computer, was used as an artificial radiation source for preliminary system tests and performance evaluations of the pro posed algorithms. Then measurement results for background radiation levels were obtained. Finally, measurements with a natural radiation source radioisotope 90Sr-90Y, were carried out. Measurement results, con ducted without and with

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Sergeev, V. А., and S. Е. Reschikoff. "Adaptive algorithms for measuring low-frequency noise parameters of semiconductor devices under mass control." Izmeritel`naya Tekhnika, no. 11 (2020): 59–64. http://dx.doi.org/10.32446/0368-1025it.2020-11-59-64.

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The solution of the problem of increasing the confidence and efficiency of quality control of semiconductor devices is considered. The analysis of conditions for measuring the power spectral density of low – frequency noise of semiconductor devices with a spectrum of the form (γ – the spectrum shape indicator) under mass quality control is presented. The error in measuring the power spectral density under the specified measurement conditions strongly depends on the value of the spectrum shape indicator. Adaptive algorithms for measuring low-frequency noise parameters are proposed for cases of

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Li, Wang, and Zheng. "Adaptive Consensus-Based Unscented Information Filter for Tracking Target with Maneuver and Colored Noise." Sensors 19, no. 14 (2019): 3069. http://dx.doi.org/10.3390/s19143069.

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Distributed state estimation plays a key role in space situation awareness via a sensor network. This paper proposes two adaptive consensus-based unscented information filters for tracking target with maneuver and colored measurement noise. The proposed filters can fulfill the distributed estimation for non-linear systems with the aid of a consensus strategy, and can reduce the impact of colored measurement noise by employing the state augmentation and measurement differencing methods. In addition, a fading factor that shrinks the predicted information state and information matrix can suppress

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Taddia, Chiara, Gianluca Mazzini, and Riccardo Rovatti. "Duty Cycle Measurement Techniques for Adaptive and Resilient Autonomic Systems." International Journal of Adaptive, Resilient and Autonomic Systems 2, no. 3 (2011): 63–87. http://dx.doi.org/10.4018/jaras.2011070105.

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When systems are deployed in environments where change is the rule rather than the exception, adaptability and resilience play a crucial role in order to preserve good quality of service. This work analyses methods that can be adopted for the duty cycle measurement of sensor-originated waveforms. These methods start from the assumption that no regular sampling is possible and thus they are naturally thought for an adaptive coexistence with other heterogeneous and variable tasks. Hence, the waveform carrying the information from low-priority sensors can be sampled only at instants that are non-

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Shangguan, Wentao, Qiurong Yan, Hui Wang, Chenglong Yuan, Bing Li, and Yuhao Wang. "Adaptive Single Photon Compressed Imaging Based on Constructing a Smart Threshold Matrix." Sensors 18, no. 10 (2018): 3449. http://dx.doi.org/10.3390/s18103449.

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We demonstrate a single-photon compressed imaging system based on single photon counting technology and compressed sensing theory. In order to cut down the measurement times and shorten the imaging time, a fast and efficient adaptive sampling method, suited for single-photon compressed imaging, is proposed. First, the pre-measured rough images are transformed into sparse bases as a priori information. Then a smart threshold matrix is designed by using large sparse coefficients of the rough image in sparse bases. The adaptive measurement matrix is obtained by modifying the original Gaussian ran

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Montgomery, Jacob M., and Josh Cutler. "Computerized Adaptive Testing for Public Opinion Surveys." Political Analysis 21, no. 2 (2013): 172–92. http://dx.doi.org/10.1093/pan/mps060.

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Survey researchers avoid using large multi-item scales to measure latent traits due to both the financial costs and the risk of driving up nonresponse rates. Typically, investigators select a subset of available scale items rather than asking the full battery. Reduced batteries, however, can sharply reduce measurement precision and introduce bias. In this article, we present computerized adaptive testing (CAT) as a method for minimizing the number of questions each respondent must answer while preserving measurement accuracy and precision. CAT algorithms respond to individuals' previous answer

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Wang, Lijun, Sisi Wang, and Wenzhi Yang. "Adaptive federated filter for multi-sensor nonlinear system with cross-correlated noises." PLOS ONE 16, no. 2 (2021): e0246680. http://dx.doi.org/10.1371/journal.pone.0246680.

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This paper presents an adaptive approach to the federated filter for multi-sensor nonlinear systems with cross-correlations between process noise and local measurement noise. The adaptive Gaussian filter is used as the local filter of the federated filter for the first time, which overcomes the performance degradation caused by the cross-correlated noises. Two kinds of adaptive federated filters are proposed, one uses a de-correlation framework as local filter, and the subfilter of the other one is defined as a Gaussian filter with correlated noises at the same-epoch, and much effort is made t

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Nazarahari, Milad, and Hossein Rouhani. "Adaptive Gain Regulation of Sensor Fusion Algorithms for Orientation Estimation with Magnetic and Inertial Measurement Units." IEEE Transactions on Instrumentation and Measurement 70 (2021): 1–13. http://dx.doi.org/10.1109/tim.2020.3033077.

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Zhou, Xin, Haishun Sun, Cong Zhang, and Qiangsheng Dai. "Optimal Placement of PMUs Using Adaptive Genetic Algorithm Considering Measurement Redundancy." International Journal of Reliability, Quality and Safety Engineering 23, no. 03 (2016): 1640001. http://dx.doi.org/10.1142/s0218539316400015.

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With the extensive use of PMUs in power system, how to implement the optimal PMU placement for complete system observability is becoming more and more significant. Against simple genetic algorithm, easy to fall into local minima, this paper proposed a simple and effective adaptive genetic algorithm, aimed at determining the optimal placement of PMUs. The proposed algorithm provides adaptive crossover and mutation probability in iterations and has better convergence and global search ability than simple genetic algorithm, confirmed in many practical applications. Generally speaking, minimum PMU

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Park, Seung Hyo, Sa Yong Chong, Hyung June Kim, and Taek Lyul Song. "Adaptive Estimation of Spatial Clutter Measurement Density Using Clutter Measurement Probability for Enhanced Multi-Target Tracking." Sensors 20, no. 1 (2019): 114. http://dx.doi.org/10.3390/s20010114.

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The point detections obtained from radars or sonars in surveillance environments include clutter measurements, as well as target measurements. Target tracking with these data requires data association, which distinguishes the detections from targets and clutter. Various algorithms have been proposed for clutter measurement density estimation to achieve accurate and robust target tracking with the point detections. Among them, the spatial clutter measurement density estimator (SCMDE) computes the sparsity of clutter measurement, which is the reciprocal of the clutter measurement density. The SC

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HOLEVA, LEE F. "RANGE ESTIMATION FROM CAMERA BLUR BY REGULARIZED ADAPTIVE IDENTIFICATION." International Journal of Pattern Recognition and Artificial Intelligence 08, no. 06 (1994): 1273–300. http://dx.doi.org/10.1142/s0218001494000644.

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One of the fundamental problems of machine vision is the estimation of object depth from perceived images. This paper describes both an apparatus and the corresponding algorithms for the passive extraction of object depth. Here passive extraction implies the processing of images acquired using only the existing illumination, in this case roughly uniform white light. Depth from defocused algorithms are extremely sensitive to image variations. Regularization, the application of a priori constraints, is employed to improve the accuracy of the range measurements. When the camera’s point spread fun

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Guan, Binglei, and Xianfeng Tang. "Multisensor decentralized nonlinear fusion using adaptive cubature information filter." PLOS ONE 15, no. 11 (2020): e0241517. http://dx.doi.org/10.1371/journal.pone.0241517.

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In nonlinear multisensor system, abrupt state changes and unknown variance of measurement noise are very common, which challenges the majority of the previously developed models for precisely known multisensor fusion techniques. In terms of this issue, an adaptive cubature information filter (CIF) is proposed by embedding strong tracking filter (STF) and variational Bayesian (VB) method, and it is extended to multi-sensor fusion under the decentralized fusion framework with feedback. Specifically, the new algorithms use an equivalent description of STF, which avoid the problem of solving Jacob

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Dong, Xiangxiang, Luigi Chisci, and Yunze Cai. "An Adaptive Filter for Nonlinear Multi-Sensor Systems with Heavy-Tailed Noise." Sensors 20, no. 23 (2020): 6757. http://dx.doi.org/10.3390/s20236757.

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Aiming towards state estimation and information fusion for nonlinear systems with heavy-tailed measurement noise, a variational Bayesian Student’s t-based cubature information filter (VBST-CIF) is designed. Furthermore, a multi-sensor variational Bayesian Student’s t-based cubature information feedback fusion (VBST-CIFF) algorithm is also derived. In the proposed VBST-CIF, the spherical-radial cubature (SRC) rule is embedded into the variational Bayes (VB) method for a joint estimation of states and scale matrix, degree-of-freedom (DOF) parameter, as well as an auxiliary parameter in the nonli

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Chiella, Antônio C. B., Bruno O. S. Teixeira, and Guilherme A. S. Pereira. "Quaternion-Based Robust Attitude Estimation Using an Adaptive Unscented Kalman Filter." Sensors 19, no. 10 (2019): 2372. http://dx.doi.org/10.3390/s19102372.

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This paper presents the Quaternion-based Robust Adaptive Unscented Kalman Filter (QRAUKF) for attitude estimation. The proposed methodology modifies and extends the standard UKF equations to consistently accommodate the non-Euclidean algebra of unit quaternions and to add robustness to fast and slow variations in the measurement uncertainty. To deal with slow time-varying perturbations in the sensors, an adaptive strategy based on covariance matching that tunes the measurement covariance matrix online is used. Additionally, an outlier detector algorithm is adopted to identify abrupt changes in

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Basturk, Halil Ibrahim. "Active Unmatched Disturbance Cancellation and Estimation by State--Derivative Feedback for Plants Modeled as an LTI System." An International Journal of Optimization and Control: Theories & Applications (IJOCTA) 8, no. 2 (2018): 237–49. http://dx.doi.org/10.11121/ijocta.01.2018.00519.

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We design adaptive algorithms for both cancellation and estimation of unknown periodic disturbance, by feedback of state--derivatives ( i.e.,} without position information for mechanical systems) for the plants which are modeled as a linear time invariant system. We consider a series of unmatched unknown sinusoidal signals as the disturbance.The first step of the design consists of the parametrization of the disturbance model and the development of observer filters.The result obtained in this step allows us to use adaptive control techniques for the solution of the problem.In order to handle t

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Yang, Yang, Quan Li, Junnan Zhang, and Yangmin Xie. "Iterative Learning-Based Path and Speed Profile Optimization for an Unmanned Surface Vehicle." Sensors 20, no. 2 (2020): 439. http://dx.doi.org/10.3390/s20020439.

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Most path-planning algorithms can generate a reasonable path by considering the kinematic characteristics of the vehicles and the obstacles in hydrographic survey activities. However, few studies consider the influence of vehicle dynamics, although excluding system dynamics may considerably damage the measurement accuracy especially when turning at high speed. In this study, an adaptive iterative learning algorithm is proposed to optimize the turning parameters, which accounts for the dynamic characteristics of unmanned surface vehicles (USVs). The resulting optimal turning radius and speed ar

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Franken, Arnoud R. C., and Paul C. Ivey. "Enhancing Flow Field Measurements Through Adaptive Multidimensional Data Sampling." Journal of Engineering for Gas Turbines and Power 128, no. 3 (2005): 518–24. http://dx.doi.org/10.1115/1.2135822.

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A way to gain insight into the flow field conditions in turbomachinery is by carrying out a series of point measurements in a cross section of the flow, for example, with a miniature multihole pressure probe. A problem commonly encountered in situations like these is the selection of a suitable measurement grid layout and density for obtaining all essential information in a cost-effective and timely manner. In order to achieve the latter, a novel adaptive multidimensional data sampling technique has been developed at Cranfield University. This paper describes the underlying principles of this

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Wang, Jie Gui. "New Method of Moving Targets Passive Tracking by Single Moving Observer Based on Measurement Data Fusion." Applied Mechanics and Materials 239-240 (December 2012): 942–45. http://dx.doi.org/10.4028/www.scientific.net/amm.239-240.942.

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Moving targets passive tracking by single moving observer is a difficult problem. A new location method based on measurement data fusion is proposed in this paper. Firstly, the adaptive passive tracking initiation algorithm is introduced. Secondly, a new data association algorithm is proposed, based on the data fusion of multiple measurements, the decision of synthetic data association is made. Finally, with the help of computer simulations, the proposed algorithms are proven to be correct and effective.

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Lu Zhou and B. Yazici. "Discretization Error Analysis and Adaptive Meshing Algorithms for Fluorescence Diffuse Optical Tomography in the Presence of Measurement Noise." IEEE Transactions on Image Processing 20, no. 4 (2011): 1094–111. http://dx.doi.org/10.1109/tip.2010.2083677.

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Mahr, Tristan J., Visar Berisha, Kan Kawabata, Julie Liss, and Katherine C. Hustad. "Performance of Forced-Alignment Algorithms on Children's Speech." Journal of Speech, Language, and Hearing Research 64, no. 6S (2021): 2213–22. http://dx.doi.org/10.1044/2020_jslhr-20-00268.

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Purpose Acoustic measurement of speech sounds requires first segmenting the speech signal into relevant units (words, phones, etc.). Manual segmentation is cumbersome and time consuming. Forced-alignment algorithms automate this process by aligning a transcript and a speech sample. We compared the phoneme-level alignment performance of five available forced-alignment algorithms on a corpus of child speech. Our goal was to document aligner performance for child speech researchers. Method The child speech sample included 42 children between 3 and 6 years of age. The corpus was force-aligned usin

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Shi, Gang, Xisheng Li, Zhe Wang, and Yanxia Liu. "A new measurement for yaw estimation of land vehicles using MARG sensors." Sensor Review 39, no. 5 (2019): 636–44. http://dx.doi.org/10.1108/sr-10-2018-0276.

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Purpose The magnetometer measurement update plays a key role in correcting yaw estimation in fusion algorithms, and hence, the yaw estimation is vulnerable to magnetic disturbances. The purpose of this study is to improve the ability of the fusion algorithm to deal with magnetic disturbances. Design/methodology/approach In this paper, an adaptive measurement equation based on vehicle status is derived, which can constrain the yaw estimation from drifting when vehicle is running straight. Using this new measurement, a Kalman filter-based fusion algorithm is constructed, and its performance is e

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Zhou, Tao, Huiling Lu, Fuyuan Hu, Hongbin Shi, Shi Qiu, and Huiqun Wang. "A New Robust Adaptive Fusion Method for Double-Modality Medical Image PET/CT." BioMed Research International 2021 (February 4, 2021): 1–18. http://dx.doi.org/10.1155/2021/8824395.

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A new robust adaptive fusion method for double-modality medical image PET/CT is proposed according to the Piella framework. The algorithm consists of the following three steps. Firstly, the registered PET and CT images are decomposed using the nonsubsampled contourlet transform (NSCT). Secondly, in order to highlight the lesions of the low-frequency image, low-frequency components are fused by pulse-coupled neural network (PCNN) that has a higher sensitivity to featured area with low intensities. With regard to high-frequency subbands, the Gauss random matrix is used for compression measuremen

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Dichev, Dimitar, Hristofor Koev, Totka Bakalova та Petr Louda. "А Меаsuring Method for Gyro-Free Determination of the Parameters of Moving Objects". Metrology and Measurement Systems 23, № 1 (2016): 107–18. http://dx.doi.org/10.1515/mms-2016-0001.

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Abstract The paper presents a new method for building measuring instruments and systems for gyro-free determination of the parameters of moving objects. To illustrate the qualities of this method, a system for measuring the roll, pitch, heel and trim of a ship has been developed on its basis. The main concept of the method is based, on one hand, on a simplified design of the base coordinate system in the main measurement channel so as to reduce the instrumental errors, and, on the other hand, on an additional measurement channel operating in parallel with the main one and whose hardware and so

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Heng, Sovannarith, Phet Aimtongkham, Van Nhan Vo, Tri Gia Nguyen, and Chakchai So-In. "Fuzzy Adaptive-Sampling Block Compressed Sensing for Wireless Multimedia Sensor Networks." Sensors 20, no. 21 (2020): 6217. http://dx.doi.org/10.3390/s20216217.

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The transmission of high-volume multimedia content (e.g., images) is challenging for a resource-constrained wireless multimedia sensor network (WMSN) due to energy consumption requirements. Redundant image information can be compressed using traditional compression techniques at the cost of considerable energy consumption. Fortunately, compressed sensing (CS) has been introduced as a low-complexity coding scheme for WMSNs. However, the storage and processing of CS-generated images and measurement matrices require substantial memory. Block compressed sensing (BCS) can mitigate this problem. Nev

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Wang, Hongjian, Ying Wang, Cun Li, Juan Li, Qing Li, and Xicheng Ban. "Adaptive Weight Update Algorithm for Target Tracking of UUV Based on Improved Gaussian Mixture Cubature Kalman Filter." Complexity 2020 (June 4, 2020): 1–12. http://dx.doi.org/10.1155/2020/7828050.

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The Gaussian mixture filter can solve the non-Gaussian problem of target tracking in complex environment by the multimode approximation method, but the weights of the Gaussian component of the conventional Gaussian mixture filter are only updated with the arrival of the measurement value in the measurement update stage. When the nonlinear degree of the system is high or the measurement value is missing, the weight of the Gauss component remains unchanged, and the probability density function of the system state cannot be accurately approximated. To solve this problem, this paper proposes an al

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Khadour, Tammam, Michel Al Saba, and Louay Saleh. "Improving bearings-only target state estimation tracking problem by using adaptive and nonlinear kalman algorithms." Indonesian Journal of Electrical Engineering and Computer Science 15, no. 1 (2019): 190. http://dx.doi.org/10.11591/ijeecs.v15.i1.pp190-198.

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<p><span style="font-family: 'Times New Roman'; font-size: 9pt; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">Finding the best estimate of the process state from noisy data is the main problem in tracking systems, many efforts and researches have been done to remove this noise. More useful information about the target’s state can be extracted from observations by using a more appropriate model for the target’s motion or using additional sensors. In this paper, we will introduce two methods to improve th

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Alimuradov, Alan K., Alexander Yu Tychkov, Andrey V. Kuzmin, Pyotr P. Churakov, Alexey V. Ageykin, and Galina V. Vishnevskaya. "Improved CEEMDAN Based Speech Signal Analysis Algorithm for Mental Disorders Diagnostic System." International Journal of Embedded and Real-Time Communication Systems 10, no. 1 (2019): 22–47. http://dx.doi.org/10.4018/ijertcs.2019010102.

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An automated algorithm for pitch frequency measurement for diagnostic systems of borderline mental disorders is developed. It is based on decomposition of a speech signal into frequency components using an adaptive method for analyzing of non-stationary signals, improved complete ensemble empirical mode decomposition with adaptive noise (improved CEEMDAN), and isolating the component containing pitch. A block diagram for the developed algorithm and a detailed mathematical description are presented. A research of the algorithm using the formed verified signal base of healthy patients, and male

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Xie, Zheng Wen. "Study on Thermogravimetry Data of Cooking Oil Tar Based on Adaptive Wavelet Analysis." Applied Mechanics and Materials 423-426 (September 2013): 2486–90. http://dx.doi.org/10.4028/www.scientific.net/amm.423-426.2486.

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Test of the combustion characteristics of cooking oil tar in pipe was conducted. Wavelet transform was introduced to the thermogravimetric data smoothing and differentiation analysis according to the experiment results, and the orthogonal test method was used to find the optimize wavelet parameter. Wavelet transform results were compared to the traditional Moving average,Gaussian Smoothing and Vondrak smoothing methods and it was proved that the signal-to-noise ratio () of the measurement is increased significantly. The kinetic parameters calculated from the original TG curves and smoothed DTG

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Orlov, Y. V. "Sliding Mode Observer-Based Synthesis of State Derivative-Free Model Reference Adaptive Control of Distributed Parameter Systems." Journal of Dynamic Systems, Measurement, and Control 122, no. 4 (2000): 725–31. http://dx.doi.org/10.1115/1.1320447.

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This paper presents control laws for distributed parameter systems of parabolic and hyperbolic types which, on the one hand ensure robustness with respect to small dynamic uncertainties and disturbances, and on the other hand, permit on-line plant parameter estimation. The novelty of the algorithms proposed is (a) in the construction of a sliding mode-based state derivative observer and (b) in the inclusion of this observer into a model reference adaptive controller which thereby regularizes the ill-posed identification problem itself. Apart from this, the controllers constructed do not suffer

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Kubal, Sharvaj, Elizabeth Lee, Chor Yong Tay, and Derrick Yong. "Multitrack Compressed Sensing for Faster Hyperspectral Imaging." Sensors 21, no. 15 (2021): 5034. http://dx.doi.org/10.3390/s21155034.

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Hyperspectral imaging (HSI) provides additional information compared to regular color imaging, making it valuable in areas such as biomedicine, materials inspection and food safety. However, HSI is challenging because of the large amount of data and long measurement times involved. Compressed sensing (CS) approaches to HSI address this, albeit subject to tradeoffs between image reconstruction accuracy, time and generalizability to different types of scenes. Here, we develop improved CS approaches for HSI, based on parallelized multitrack acquisition of multiple spectra per shot. The multitrack

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Battiston, Adrian, Inna Sharf, and Meyer Nahon. "Attitude estimation for collision recovery of a quadcopter unmanned aerial vehicle." International Journal of Robotics Research 38, no. 10-11 (2019): 1286–306. http://dx.doi.org/10.1177/0278364919867397.

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An extensive evaluation of attitude estimation algorithms in simulation and experiments is performed to determine their suitability for a collision recovery pipeline of a quadcopter unmanned aerial vehicle. A multiplicative extended Kalman filter (MEKF), unscented Kalman filter (UKF), complementary filter, [Formula: see text] filter, and novel adaptive varieties of the selected filters are compared. The experimental quadcopter uses a PixHawk flight controller, and the algorithms are implemented using data from only the PixHawk inertial measurement unit (IMU). Performance of the aforementioned

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Miruthula, D., and Ramachandran Rajeswari. "Synchro Phasor Measurement Based Fault Analysis of a Parallel Transmission Line." Advanced Materials Research 984-985 (July 2014): 996–1004. http://dx.doi.org/10.4028/www.scientific.net/amr.984-985.996.

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This paper presents a new method to classify transmission line shunt faults and determine the fault location using phasor data of the transmission system. Most algorithms employed for analyzing fault data require that the fault type to be classified. The older fault-type classification algorithms are inefficient because they are not effective under certain operating conditions of the power system and may not be able to accurately select the faulted transmission line if the same fault recorder monitors multiple lines. An intelligent techniques described in this paper is used to precisely detect

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Guo, Yanbing, Lingjuan Miao, and Yusen Lin. "A Novel EM Implementation for Initial Alignment of SINS Based on Particle Filter and Particle Swarm Optimization." Mathematical Problems in Engineering 2019 (February 20, 2019): 1–12. http://dx.doi.org/10.1155/2019/6793175.

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For nonlinear systems in which the measurement noise parameters vary over time, adaptive nonlinear filters can be applied to precisely estimate the states of systems. The expectation maximization (EM) algorithm, which alternately takes an expectation- (E-) step and a maximization- (M-) step, has been proposed to construct a theoretical framework for the adaptive nonlinear filters. Previous adaptive nonlinear filters based on the EM employ analytical algorithms to develop the two steps, but they cannot achieve high filtering accuracy because the strong nonlinearity of systems may invalidate the

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Wang, Di, Hua Liu, and Xiang Cheng. "A Miniature Binocular Endoscope with Local Feature Matching and Stereo Matching for 3D Measurement and 3D Reconstruction." Sensors 18, no. 7 (2018): 2243. http://dx.doi.org/10.3390/s18072243.

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As the traditional single camera endoscope can only provide clear images without 3D measurement and 3D reconstruction, a miniature binocular endoscope based on the principle of binocular stereoscopic vision to implement 3D measurement and 3D reconstruction in tight and restricted spaces is presented. In order to realize the exact matching of points of interest in the left and right images, a novel construction method of the weighted orthogonal-symmetric local binary pattern (WOS-LBP) descriptor is presented. Then a stereo matching algorithm based on Gaussian-weighted AD-Census transform and im

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Jiao, Hong, Junhui Liu, Kathleen Haynie, Ada Woo, and Jerry Gorham. "Comparison Between Dichotomous and Polytomous Scoring of Innovative Items in a Large-Scale Computerized Adaptive Test." Educational and Psychological Measurement 72, no. 3 (2011): 493–509. http://dx.doi.org/10.1177/0013164411422903.

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This study explored the impact of partial credit scoring of one type of innovative items (multiple-response items) in a computerized adaptive version of a large-scale licensure pretest and operational test settings. The impacts of partial credit scoring on the estimation of the ability parameters and classification decisions in operational test settings were explored in one real data analysis and two simulation studies when two different polytomous scoring algorithms, automated polytomous scoring and rater-generated polytomous scoring, were applied. For the real data analyses, the ability esti

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Pei, Wei, Yong Ying Zhu, S. X. Liu, and J. M. Wen. "Three-Dimensional Measurement System Based on Micro Stereovision." Key Engineering Materials 609-610 (April 2014): 1189–94. http://dx.doi.org/10.4028/www.scientific.net/kem.609-610.1189.

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With vision feedback the binocular micro stereovision system based on stereo light microscope (SLM) makes it possible to achieve 2D/3D high accuracy auto-positioning, 3D information extraction, 3D shape reconstruction and 3D measurement. Therefore, it is extensively used in micro robot navigation, micromanipulation, micro assembly and bioengineering, etc. To improve the key problems of low accuracy, refraction and occlusion in micro stereovision measurement, a novel micro stereo vision system is built based on optical theory and digital image processing. Then, the nonlinear correlation between

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Liu, Hongqiang, Zhongliang Zhou, and Lei Yu. "Maneuvering Acceleration Estimation Algorithm Using Doppler Radar Measurement." Mathematical Problems in Engineering 2018 (June 4, 2018): 1–13. http://dx.doi.org/10.1155/2018/4984186.

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An algorithm to estimate the tangential and normal accelerations directly using the Doppler radar measurement in an online closed loop form is proposed. Specific works are as follows: first, the tangential acceleration and normal acceleration are taken as the state variables to establish a linear state transition equation; secondly, the decorrelation unbiased conversion measurement Kalman filter (DUCMKF) algorithm is proposed to deal with the strongly nonlinear measurement equation; thirdly, the geometric relationship between the range rate and the velocity direction angle is used to obtain tw

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Galvanauskas, Vytautas, Rimvydas Simutis, and Vygandas Vaitkus. "Adaptive Control of Biomass Specific Growth Rate in Fed-Batch Biotechnological Processes. A Comparative Study." Processes 7, no. 11 (2019): 810. http://dx.doi.org/10.3390/pr7110810.

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This article presents a comparative study on the development and application of two distinct adaptive control algorithms for biomass specific growth rate control in fed-batch biotechnological processes. A typical fed-batch process using Escherichia coli for recombinant protein production was selected for this research. Numerical simulation results show that both developed controllers, an adaptive PI controller based on the gain scheduling technique and a model-free adaptive controller based on the artificial neural network, delivered a comparable control performance and are suitable for applic

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