Robust identification of pneumatic servo actuators in the real situations

Robust Statistics

Huber, P. J. (1981) · Wiley Series in Probability and Statistics · doi:10.1002/0471725250 · Cited by 7,066

Outliers in Statistical Data

BARNETT, V. D., Lewis, T., & Abeles, F. F. (1979) · Physics Today · doi:10.1063/1.2995737 · Cited by 2,834

Outliers in Statistical Data.

Atkinson, A. C., BARNETT, V. D., & Lewis, T. (1995) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.2307/2983451 · Cited by 1,693

1987 american control conference

(1987) · IEEE Control Systems Magazine · doi:10.1109/mcs.1987.1105260 · Cited by 1,402

Theory of Robot Control

(1996) · Communications and control engineering/Communications and control engineering series · doi:10.1007/978-1-4471-1501-4 · Cited by 1,008

Outliers in Statistical Data.

Freeman, J., Barnett, V., & Lewis, T. (1995) · Journal of the Operational Research Society · doi:10.2307/3009915 · Cited by 729

Robust bayesian estimation for the linear model and robustifying the Kalman filter

Masreliez, C. J., & Martin, R. D. (1977) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1977.1101538 · Cited by 411

Adaptive Control

Landau, I. D., Lozano, R., M’Saad, M., Modestino, J. W., Fettweis, A., Massey, J. L., Thoma, M., Sontag, E. D., & Dickinson, B. (1998) · Cited by 373

Fluid power control

Blackburn, J. F., Reethof, G., & Shearer, J. L. (1960) · Medical Entomology and Zoology · Cited by 280

Adaptive Control

Landau, I. D., Lozano, R., & M’Saad, M. (1998) · Communications and control engineering/Communications and control engineering series · doi:10.1007/978-0-85729-343-5 · Cited by 251

Deep learning and its applications to machine health monitoring

Zhao, R., Yan, R., Chen, Z., Mao, K., Wang, P., & Gao, R. X. (2019) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2018.05.050 · Cited by 2,894

A hybrid PSO–BFO evolutionary algorithm for optimization of fused deposition modelling process parameters

Raju, M. S. S., Gupta, M. K., Bhanot, N., & Sharma, V. S. (2018) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-018-1420-0 · Cited by 161

State and parameter joint estimation of linear stochastic systems in presence of faults and non‐Gaussian noises

Stojanović, V., He, S., & Zhang, B. (2020) · International Journal of Robust and Nonlinear Control · doi:10.1002/rnc.5131 · Cited by 126

A review on recent research trends in servo pneumatic positioning systems

Saravanakumar, D., Mohan, B., & Muthuramalingam, T. (2017) · Precision Engineering · doi:10.1016/j.precisioneng.2017.01.014 · Cited by 121

Robust Kalman filtering for nonlinear multivariable stochastic systems in the presence of non‐Gaussian noise

Stojanović, V., & Nedić, N. N. (2015) · International Journal of Robust and Nonlinear Control · doi:10.1002/rnc.3319 · Cited by 116

Joint state and parameter robust estimation of stochastic nonlinear systems

Stojanović, V., & Nedić, N. N. (2015) · International Journal of Robust and Nonlinear Control · doi:10.1002/rnc.3490 · Cited by 113

Robust identification for fault detection in the presence of non-Gaussian noises: application to hydraulic servo drives

Stojanovic, V., & Prsic, D. (2020) · Nonlinear Dynamics · doi:10.1007/s11071-020-05616-4 · Cited by 109

Adaptive Input Design for Identification of Output Error Model with Constrained Output

Stojanović, V., & Filipović, V. (2013) · Circuits Systems and Signal Processing · doi:10.1007/s00034-013-9633-0 · Cited by 109

Data-driven control of hydraulic servo actuator: An event-triggered adaptive dynamic programming approach

Djordjevic, V., Tao, H., Song, X., He, S., Gao, W., & Stojanovic, V. (2023) · Mathematical Biosciences and Engineering · doi:10.3934/mbe.2023376 · Cited by 107

Robust identification of OE model with constrained output using optimal input design

Stojanović, V., & Nedić, N. N. (2015) · Journal of the Franklin Institute · doi:10.1016/j.jfranklin.2015.12.007 · Cited by 105

Optimal experiment design for identification of ARX models with constrained output in non-Gaussian noise

Stojanović, V., Nedić, N. N., Pršić, D., & Dubonjić, L. (2016) · Applied Mathematical Modelling · doi:10.1016/j.apm.2016.02.014 · Cited by 105

Periodic event-triggered resilient control for cyber-physical systems under denial-of-service attacks

Sun, Y., & Yang, G. (2018) · Journal of the Franklin Institute · doi:10.1016/j.jfranklin.2018.06.009 · Cited by 103

Identification of time‐varying OE models in presence of non‐Gaussian noise: Application to pneumatic servo drives

Stojanović, V., & Nedić, N. N. (2016) · International Journal of Robust and Nonlinear Control · doi:10.1002/rnc.3544 · Cited by 100

Application of cuckoo search algorithm to constrained control problem of a parallel robot platform

Stojanovic, V., Nedic, N., Prsic, D., Dubonjic, L., & Djordjevic, V. (2016) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-016-8627-z · Cited by 94

Optimal cascade hydraulic control for a parallel robot platform by PSO

Nedić, N. N., Pršić, D., Dubonjić, L., Stojanović, V., & Djordjevic, V. (2014) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-014-5735-5 · Cited by 93

Data-driven control of hydraulic servo actuator based on adaptive dynamic programming

Djordjevic, V., Stojanović, V., Tao, H., Song, X., He, S., & Gao, W. (2022) · Discrete and Continuous Dynamical Systems - S · doi:10.3934/dcdss.2021145 · Cited by 93

Optimal control of hydraulically driven parallel robot platform based on firefly algorithm

Nedić, N. N., Stojanović, V., & Djordjevic, V. (2015) · Nonlinear Dynamics · doi:10.1007/s11071-015-2252-5 · Cited by 91

A Nature Inspired Parameter Tuning Approach to Cascade Control for Hydraulically Driven Parallel Robot Platform

Stojanović, V., & Nedić, N. N. (2015) · Journal of Optimization Theory and Applications · doi:10.1007/s10957-015-0706-z · Cited by 90

Factorized discriminative conditional variational auto-encoder for radar HRRP target recognition

Du, C., Chen, B., Xu, B., Guo, D., & Liu, H. (2019) · Signal Processing · doi:10.1016/j.sigpro.2019.01.006 · Cited by 85

Fuzzy Logic-Driven Variable Time-Scale Prediction-Based Reinforcement Learning for Robotic Multiple Peg-in-Hole Assembly

Hou, Z., Li, Z., Hsu, C., Zhang, K., & Xu, J. L. (2020) · IEEE Transactions on Automation Science and Engineering · doi:10.1109/tase.2020.3024725 · Cited by 80

Weighted preliminary-summation-based principal component analysis for non-Gaussian processes

Li, N., Guo, S., & Wang, Y. (2019) · Control Engineering Practice · doi:10.1016/j.conengprac.2019.03.015 · Cited by 52

Parametric system identification and robust controller design for liquid–liquid heat exchanger system

Gupta, S. D., Gupta, R., & Padhee, S. (2018) · IET Control Theory and Applications · doi:10.1049/iet-cta.2017.1128 · Cited by 50

Input attribute optimization for thermal deformation of machine-tool spindles using artificial intelligence

Maurya, S. N., Luo, W., Panigrahi, B., Negi, P., & Wang, P.-T. (2024) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-024-02350-1 · Cited by 48

Residual symmetry, Bäcklund transformation and CRE solvability of a ( $$\mathbf{2}{\varvec{+}}{} \mathbf{1}$$ 2 + 1 )-dimensional nonlinear system

Zhao, Z., & Han, B. (2018) · Nonlinear Dynamics · doi:10.1007/s11071-018-4371-2 · Cited by 42

Negotiating team formation using deep reinforcement learning

Bachrach, Y., Everett, R., Hughes, E., Lazaridou, A., Leibo, J. Z., Lanctot, M., Johanson, M., Czarnecki, W. M., & Graepel, T. (2020) · Artificial Intelligence · doi:10.1016/j.artint.2020.103356 · Cited by 43

Dynamic relationship analysis between NAFTA stock markets using nonlinear, nonparametric, non-stationary methods

Polanco-Martínez, J. M. (2019) · Nonlinear Dynamics · doi:10.1007/s11071-019-04974-y · Cited by 38

Analysis-synthesis dictionary pair learning and patch saliency measure for image fusion

Zhang, Y., Yang, M., Li, N., & Yu, Z. (2019) · Signal Processing · doi:10.1016/j.sigpro.2019.107327 · Cited by 38

Path Following of Underactuated Unmanned Surface Vehicle Based on Trajectory Linearization Control with Input Saturation and External Disturbances

Qiu, B., Wang, G., Fan, Y., Mu, D., & Sun, X. (2020) · International Journal of Control Automation and Systems · doi:10.1007/s12555-019-0659-3 · Cited by 37

Parameter estimation methods for time‐invariant continuous‐time systems from dynamical discrete output responses based on the Laplace transforms

Ibrahim, K. A., & Ding, F. (2024) · International Journal of Adaptive Control and Signal Processing · doi:10.1002/acs.3871 · Cited by 35

Wiener–Hammerstein nonlinear system identification using spectral analysis

Brouri, A. (2022) · International Journal of Robust and Nonlinear Control · doi:10.1002/rnc.6135 · Cited by 35

An Adversary-Resilient Doubly Compressed Diffusion LMS Algorithm for Distributed Estimation

Zayyani, H., Oruji, F., & Fijalkow, I. (2022) · Circuits Systems and Signal Processing · doi:10.1007/s00034-022-02072-w · Cited by 27

Finite-Time Control of Uncertain Fractional-Order Positive Impulsive Switched Systems with Mode-Dependent Average Dwell Time

Liu, L., Cao, X., Fu, Z., Song, S., & Xing, H. (2018) · Circuits Systems and Signal Processing · doi:10.1007/s00034-018-0752-5 · Cited by 27

Solving a reliability-performance balancing problem for control systems with degrading actuators under model predictive control framework

Zhang, J., Liu, T., & Qiao, J. (2022) · Journal of the Franklin Institute · doi:10.1016/j.jfranklin.2022.04.007 · Cited by 25

Set-Membership Filtering for 2-D Systems Under Uniform Quantization and Weighted Try-Once-Discard Protocol

Li, M., Liang, J., & Qiu, J. (2023) · IEEE Transactions on Circuits & Systems II Express Briefs · doi:10.1109/tcsii.2023.3263201 · Cited by 24

Adaptive complex-valued dictionary learning: Application to fMRI data analysis

Iqbal, A., Meziane, M. N., Seghouane, A., & Abed‐Meraim, K. (2019) · Signal Processing · doi:10.1016/j.sigpro.2019.107263 · Cited by 21

Analysis of financial stock markets through the multiscale cross-distribution entropy based on the Tsallis entropy

Wang, Y., & Shang, P. (2018) · Nonlinear Dynamics · doi:10.1007/s11071-018-4429-1 · Cited by 21

Monitoring of potato crops based on multispectral image feature extraction with vegetation indices

Meivel, S., & Maheswari, S. U. (2022) · Multidimensional Systems and Signal Processing · doi:10.1007/s11045-021-00809-5 · Cited by 20

Spike Detection Based on the Adaptive Time–Frequency Analysis

Mohammadi, M., Khan, N. A., Hassanpour, H., & Mohammed, A. H. (2020) · Circuits Systems and Signal Processing · doi:10.1007/s00034-020-01427-5 · Cited by 20

The optimization of accuracy and efficiency for multistage precision grinding process with an improved particle swarm optimization algorithm

Chen, Z., Li, X., Zhu, Z., Zhao, Z., Wang, L., Jiang, S., & Rong, Y. K. (2020) · International Journal of Advanced Robotic Systems · doi:10.1177/1729881419893508 · Cited by 19

Elastodynamic modeling and parameter sensitivity analysis of a parallel manipulator with articulated traveling plate

Lian, B., Wang, L., & Wang, X. V. (2019) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-018-03257-x · Cited by 19

A non-linear non-Gaussian filtering framework based on the Gaussian noise model jump assumption

He, J., Peng, B., & Wang, G. (2025) · Automatica · doi:10.1016/j.automatica.2025.112360 · Cited by 18

A Constrained Predictive Controller for AUV and Computational Optimization Using Laguerre Functions in Unknown Environments

Rashidi, A. J., Karimi, B., & Khodaparast, A. (2019) · International Journal of Control Automation and Systems · doi:10.1007/s12555-018-0946-4 · Cited by 18

One wheel vehicle real world control based on interval type 2 fuzzy controller

Chiu, C.-H., & Hung, Y.-T. (2020) · Mechatronics · doi:10.1016/j.mechatronics.2020.102387 · Cited by 18

Cauchy kernel minimum error entropy centralized fusion filter

Feng, X., Wu, C., & Ge, Q. (2024) · Signal Processing · doi:10.1016/j.sigpro.2024.109465 · Cited by 17

Steady-state speed sensor fault detection in induction motors with uncertain parameters: A matter of algebraic equations

Verrelli, C. M., Lorenzani, E., Fornari, R., Mengoni, M., & Zarri, L. (2018) · Control Engineering Practice · doi:10.1016/j.conengprac.2018.08.016 · Cited by 17

Autonomous foraging with a pack of robots based on repulsion, attraction and influence

Ordaz-Rivas, E. D. J., Rodríguez, A., & Torres‐Treviño, L. (2021) · Autonomous Robots · doi:10.1007/s10514-021-09994-5 · Cited by 16

Orthogonal Periodic Sequences for the Identification of Functional Link Polynomial Filters

Carini, A., Orcioni, S., Terenzi, A., & Cecchi, S. (2020) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2020.3021244 · Cited by 16

Automatic detection of Voice Onset Time in voiceless plosives using gated recurrent units

Arias‐Vergara, T., Vélez, P. A., Vásquez-Correa, J. C., Nöth, E., Schuster, M., Rátiva, M. C. G., & Orozco‐Arroyave, J. R. (2020) · Digital Signal Processing · doi:10.1016/j.dsp.2020.102779 · Cited by 15

Collective Tasks for a Flock of Robots Using Influence Factor

Ordaz-Rivas, E. D. J., Rodríguez, A., Aguilera-Ruíz, M., & Torres‐Treviño, L. (2018) · Journal of Intelligent & Robotic Systems · doi:10.1007/s10846-018-0941-2 · Cited by 14

A Room Impulse Response Measurement Method Robust Towards Nonlinearities Based on Orthogonal Periodic Sequences

Carini, A., Cecchi, S., Terenzi, A., & Orcioni, S. (2021) · IEEE/ACM Transactions on Audio Speech and Language Processing · doi:10.1109/taslp.2021.3120595 · Cited by 14

PID: a PDF-induced distance based on permutation cross-distribution entropy

He, J., Shang, P., & Zhang, Y. (2019) · Nonlinear Dynamics · doi:10.1007/s11071-019-05051-0 · Cited by 14

A generalized two-stage tensor denoising method based on the prior of the noise location and rank

Zhang, W., Fan, Y., Song, Y., Tang, K., & Li, B. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.124809 · Cited by 13

An Improved Consistent Subspace Identification Method Using Parity Space for State-space Models

Hou, J., Chen, F., Li, P., Zhu, Z., & Liu, F. (2019) · International Journal of Control Automation and Systems · doi:10.1007/s12555-018-0499-6 · Cited by 13

Time average estimation in the fraction-of-time probability framework

Dehay, D., Leśkow, J., & Napolitano, A. (2018) · Signal Processing · doi:10.1016/j.sigpro.2018.07.005 · Cited by 12

Robust self-triggered MPC with fast convergence for constrained linear systems

Dai, L., Yang, F., Qiang, Z., & Xia, Y. (2019) · Journal of the Franklin Institute · doi:10.1016/j.jfranklin.2018.12.009 · Cited by 11

Homoclinic breather wave, rouge wave and interaction solutions for a (3+1)-dimensional KdV-type equation

Na, L., & Liu, Y. (2018) · Physica Scripta · doi:10.1088/1402-4896/aaf654 · Cited by 10

Modified multiplicative quaternion cubature Kalman filter for attitude estimation

Qiu, Z., & Qian, H. (2018) · International Journal of Adaptive Control and Signal Processing · doi:10.1002/acs.2895 · Cited by 10

Improvement in Monte Carlo localization using information theory and statistical approaches

Mohseni, A., Duchaine, V., & Wong, T. (2024) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2024.107897 · Cited by 9

Kinematic Calibration of a Novel Two-Axis Solar Tracker

Wu, J., Ye, H., & Tian, Y. (2025) · IEEE Transactions on Automation Science and Engineering · doi:10.1109/tase.2024.3510745 · Cited by 9

Reconstruction of gapped missing samples based on instantaneous frequency and instantaneous amplitude estimation

Khan, N. A., & Ali, S. (2021) · Signal Processing · doi:10.1016/j.sigpro.2021.108429 · Cited by 9

Localization of underground pipe jacking machinery: A reliable, real-time and robust INS/OD solution

Zhao, S., Zhou, Z., Zhang, C., Wu, J., Liu, F., & Shi, G. (2023) · Control Engineering Practice · doi:10.1016/j.conengprac.2023.105711 · Cited by 8

A Rapid Base Parameter Physical Feasibility Test Algorithm for Industrial Robot Manipulator Identification Using a Recurrent Neural Network

Huang, H.-L., Cheng, M.-Y., & Huang, T.-Y. (2023) · IEEE Access · doi:10.1109/access.2023.3344490 · Cited by 8

Mixture generalized minimum error entropy-based distributed lattice Kalman filter

Jiao, Y., Niu, J., Zhao, H., & Lou, T. (2024) · Digital Signal Processing · doi:10.1016/j.dsp.2024.104508 · Cited by 8

Flock of Robots with Self-Cooperation for Prey-Predator Task

Ordaz-Rivas, E. D. J., Rodríguez, A., & Torres‐Treviño, L. (2021) · Journal of Intelligent & Robotic Systems · doi:10.1007/s10846-020-01283-0 · Cited by 8

A measurement modified centered error entropy cubature Kalman filter for integrated INS/GNSS

Yang, B., Wang, H., Song, L., & Liu, Z. (2024) · Measurement · doi:10.1016/j.measurement.2024.115745 · Cited by 7

Enhanced control in time-delay processes: Diagnostic, monitoring, and self-tuning strategies for the filtered smith predictor in response to model-plant mismatch and abrupt load disturbances

Giraldo, S. A. C., Melo, P. A., & Secchi, A. R. (2024) · Control Engineering Practice · doi:10.1016/j.conengprac.2024.105869 · Cited by 7

A Non-Parametric Approach for Identification of Parameter Varying Hammerstein Systems

Tehrani, E. S., & Kearney, R. E. (2022) · IEEE Access · doi:10.1109/access.2022.3141704 · Cited by 7

Robot Dynamic Identification Based on Data Weighting Protection and Nonlinear Friction Separation

Xu, T. L., Tuo, H., Wang, C., Zhang, Z., Fan, J., Zhu, Y., & Zhao, J. (2025) · IEEE/ASME Transactions on Mechatronics · doi:10.1109/tmech.2025.3561579 · Cited by 7

Exploring the use of two servo-valves for servo-pneumatic control

Dolleman, P. C. F. E. M., Carneiro, J. F., & de Almeida, F. G. (2018) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-018-2230-4 · Cited by 6

An integrated positioning method with IMU/UWB based on geometric constraints of foot-to-foot distances

Zhang, Q., Xu, X., Shi, F., Shu, L., & Wang, J. (2024) · Measurement · doi:10.1016/j.measurement.2024.115771 · Cited by 5

Bayesian monitoring of machining processes using non-intrusive sensing and on-machine comparator measurement

Papananias, M. (2025) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-025-15174-x · Cited by 5

A Novel Feature-Fusion-Based Sparse Masked Attention Network for Acoustic Echo Cancellation Using Wavelet and STFT Synergies

Ishwarya, V. S., & Kothandaraman, M. (2024) · Circuits Systems and Signal Processing · doi:10.1007/s00034-024-02955-0 · Cited by 5

Bayesian estimation of fractional difference parameter in ARFIMA models and its application

Miyandoab, M. F., Nasiri, P., & Mosammam, A. M. (2023) · Information Sciences · doi:10.1016/j.ins.2023.01.108 · Cited by 5

Input delay compensation of nonlinear systems with uncertain time-varying parameters

Jain, A. K. (2024) · European Journal of Control · doi:10.1016/j.ejcon.2024.101100 · Cited by 5

Half-quadratic Student's t-based kernel adaptive filter based on multikernel Nyström method

Cui, M., Lin, D., Zheng, Y., & Wang, S. (2025) · Digital Signal Processing · doi:10.1016/j.dsp.2025.105260 · Cited by 5

Hilbert spectrum analysis of piecewise stationary signals and its application to texture classification

Yang, Z., Zhang, Q., Zhou, F., & Yang, L. (2018) · Digital Signal Processing · doi:10.1016/j.dsp.2018.07.020 · Cited by 5

Product beamforming and nested array in tandem for enhanced sonar performance

Pillai, S. V., Santhanakrishnan, T., Kumar, N. S., & Rajesh, R. (2022) · Multidimensional Systems and Signal Processing · doi:10.1007/s11045-022-00825-z · Cited by 5

Robust recursive estimation for the errors-in-variables nonlinear systems with impulsive noise

Wang, X., & Zhu, F. (2025) · Scientific Reports · doi:10.1038/s41598-025-89969-z · Cited by 4

A New Robust Identification Algorithm for Hammerstein-Like System Using Identification Error Structure

Li, Z., Ma, L., & Wang, Y. (2022) · IEEE Access · doi:10.1109/access.2022.3158941 · Cited by 4

Multiscale Reflection Component Based Weakly Illuminated Nighttime Image Enhancement

Singh, N., & Bhandari, A. K. (2022) · Circuits Systems and Signal Processing · doi:10.1007/s00034-022-02080-w · Cited by 4

Robust Gaussian Mixture Modeling: A $\mathcal{K}$-Divergence Based Approach

Kenig, O., Todros, K., & Adalı, T. (2024) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2024.3426965 · Cited by 4

RobustH∞Deep Neural Network-Based Filter Design of Nonlinear Stochastic Signal Systems

Chen, B., Wu, P.-H., & Lee, M. (2021) · IEEE Access · doi:10.1109/access.2021.3133899 · Cited by 4

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Ji, B., Sun, X., Chen, P., Wang, S., Song, S., & He, B. (2024) · Electronics · doi:10.3390/electronics13234727 · Cited by 3

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Liang, J., Zhao, Q., Zhao, W. G., Yang, X., Ren, S., & Cai, W. (2025) · Nonlinear Dynamics · doi:10.1007/s11071-025-11066-7 · Cited by 3

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Sanim, K. R. I., English, C. M., Kitzhaber, Z. B., Kalaitzakis, M., Vitzilaios, N. I., Myrick, M. L., Hodgson, M. E., & Richardson, T. L. (2023) · Journal of Intelligent & Robotic Systems · doi:10.1007/s10846-023-01880-9 · Cited by 3

Drift suppression method based on signal stability detection and adaptive Kalman filter for NMR sensor

Wang, Q., Liu, Z., Wu, Z., Wang, J., Qu, C., & Li, J. (2024) · Digital Signal Processing · doi:10.1016/j.dsp.2024.104812 · Cited by 3

A new grey prediction model for the return material authorization process in the TFT-LCD industry

Li, D., Yeh, C.-W., Chen, C.-C., & Wang, Y.-T. (2018) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-018-1754-y · Cited by 3

Real-time filtering with sparse variations for head motion in magnetic resonance imaging

Weller, D. S., Noll, D. C., & Fessler, J. A. (2018) · Signal Processing · doi:10.1016/j.sigpro.2018.12.001 · Cited by 3

Filter-Free Parameter Estimation Method for Continuous-Time Systems

Li, Z., & Shen, D. (2023) · IEEE Transactions on Automation Science and Engineering · doi:10.1109/tase.2023.3307758 · Cited by 2

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Thannoon, H. H., & Hashim, I. A. (2023) · Circuits Systems and Signal Processing · doi:10.1007/s00034-023-02539-4 · Cited by 2

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Sheng, L., Guo, Y., Qian, J., & Qian, G. (2025) · Circuits Systems and Signal Processing · doi:10.1007/s00034-025-03136-3 · Cited by 2

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Jiao, Y., Chang, S., Chen, Z., Lou, T., Li, X., & Niu, C. (2025) · Circuits Systems and Signal Processing · doi:10.1007/s00034-025-03240-4 · Cited by 2

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Shi, L. Q., & Zhao, H. (2018) · Circuits Systems and Signal Processing · doi:10.1007/s00034-018-0761-4 · Cited by 2

A Quaternionic Extension Algorithm of the Nonlinear Transformation for Active Impulsive Noise Control

Zhang, B., Chen, X., & Zhong, B. (2024) · Circuits Systems and Signal Processing · doi:10.1007/s00034-024-02863-3 · Cited by 1

Gaussian Filtering With Stochastically Composed Current and Past Measurements

Naik, A. K., Garg, N., Upadhyay, P. K., & Singh, A. K. (2025) · IEEE Transactions on Automation Science and Engineering · doi:10.1109/tase.2025.3639904 · Cited by 1

A repetitive learning based fractional order parameter optimization algorithm for extended Wiener systems with backlash nonlinearity subject to binary-valued data

Gong, Y., Feng, Y., Lu, X., & Li, L. (2026) · Scientific Reports · doi:10.1038/s41598-026-48069-2 · Cited by 1

Identification of a nonlinear rational model based on bias compensated multi-innovation stochastic gradient algorithm

Jing, S., Liu, R. R., & Chen, L. (2022) · Automatika · doi:10.1080/00051144.2022.2087843 · Cited by 1

An automated framework to evaluate soft skills using posture and disfluency detection

Gulati, V., Dwivedi, S., Kumar, D., Wadhwa, J., Dhingra, D., & Hemanth, D. J. (2023) · Machine Vision and Applications · doi:10.1007/s00138-023-01431-0 · Cited by 1

JOINT ESTIMATION OF STATES AND PARAMETERS OF LINEAR SYSTEMS WITH PARAMETER FAULTS UNDER NON-GAUSSIAN NOISES

Stojanović, V., Pršić, D., & Dubonjić, L. (2020) · Facta Universitatis Series Automatic Control and Robotics · doi:10.22190/fuacr1902113s · Cited by 1

Model-Based Bayesian Compressive Sensing of Non-stationary Images Using a Wavelet-Domain Triplet Markov Fields Model

Torkamani, R., & Sadeghzadeh, R. A. (2020) · Circuits Systems and Signal Processing · doi:10.1007/s00034-020-01484-w · Cited by 1

Identification of time‐varying OE models in presence of non‐Gaussian noise: Application to pneumatic servo drives

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