Variable selection of high-dimensional non-parametric nonlinear systems: A way to avoid the curse of dimensionality. - Er-Wei Bai; Changmin Cheng; Wen-Xiao Zhao; Han-Fu Chen (CDC, 2017)

Ranking Variables Based on Goodness of Fits in Nonlinear Nonparametric System Identification. - Er-Wei Bai; Changmin Cheng (MED, 2018)

Impulse response function identification of linear mechanical systems based on Kautz basis expansion with multiple poles. - Changming Cheng; Zhike Peng; Xingjian Dong; Wenming Zhang; Guang Meng (Int. J. Syst. Sci., 2018)

Variable Selection for a Nonparametric Nonlinear System by Directional Regression. - Changming Cheng; Er-Wei Bai (CDC, 2019)

Variable selection of high-dimensional non-parametric nonlinear systems by derivative averaging to avoid the curse of dimensionality. - Er-Wei Bai; Changming Cheng; Wen-Xiao Zhao (Autom., 2019)

Ranking the importance of variables in nonlinear system identification. - Changming Cheng; Er-Wei Bai (Autom., 2019)

Consistent Variable Selection for a Nonparametric Nonlinear System by Inverse and Contour Regressions. - Changming Cheng; Er-Wei Bai; Zhike Peng (IEEE Trans. Autom. Control., 2019)

Detecting the Early Damages in Structures With Nonlinear Output Frequency Response Functions and the CNN-LSTM Model. - Baoxuan Zhao; Changming Cheng; Zhike Peng; Xingjian Dong; Guang Meng (IEEE Trans. Instrum. Meas., 2020)

Variable selection based on squared derivative averages. - Changming Cheng; Er-Wei Bai (Autom., 2021)

Identification of Switched Linear Systems: Persistence of Excitation and Numerical Algorithms. - Bi-Qiang Mu; Tianshi Chen 001; Changming Cheng; Er-Wei Bai (CoRR, 2021)

Variable Selection According to Goodness of Fit in Nonparametric Nonlinear System Identification. - Changming Cheng; Er-Wei Bai (IEEE Trans. Autom. Control., 2021)

Hybrid Pre-Training Strategy for Deep Denoising Neural Networks and Its Application in Machine Fault Diagnosis. - Baoxuan Zhao; Changming Cheng; Zhike Peng; Qingbo He; Guang Meng (IEEE Trans. Instrum. Meas., 2021)

Persistence of excitation for identifying switched linear systems. - Bi-Qiang Mu; Tianshi Chen 001; Changming Cheng; Er-Wei Bai (Autom., 2022)

Identification of Sparse Volterra Systems: An Almost Orthogonal Matching Pursuit Approach. - Changming Cheng; Er-Wei Bai; Zhike Peng (IEEE Trans. Autom. Control., 2022)

Relation-Aware Attentive Neural Processes Model for Remaining Useful Life Prediction. - Junzhong Lu; Changming Cheng; Baoxuan Zhao; Zhike Peng (IEEE Trans. Instrum. Meas., 2022)

An Instance and Feature-Based Hybrid Transfer Model for Fault Diagnosis of Rotating Machinery With Different Speeds. - Baoxuan Zhao; Changming Cheng; Guanzhen Zhang; Miaomiao Lin; Zhike Peng; Guang Meng (IEEE Trans. Instrum. Meas., 2022)

An Unsupervised Condition Monitoring Method for Rolling Bearings Based on Compound Feature Selection and Multistep-Aware BiGRU-VAE. - Xinyu Li; Changming Cheng; Guanzhen Zhang; Zhike Peng (IEEE Trans. Instrum. Meas., 2023)

Semisupervised Fault Diagnosis of Gearbox Using Weighted Graph-Based Label Propagation and Virtual Adversarial Training. - Duo Shan; Changming Cheng; Lingjian Li; Zhike Peng; Qingbo He (IEEE Trans. Instrum. Meas., 2023)

A Nonlinearity-Sensitive Approach for Early Damage Detection Using NOFRFs and the Hybrid-LSTM Model. - Shangyu Zhao; Changming Cheng; Guanzhen Zhang; Miaomiao Lin; Zhike Peng; Guang Meng (IEEE Trans. Instrum. Meas., 2023)

Hybrid Semi-Supervised Learning for Rotating Machinery Fault Diagnosis Based on Grouped Pseudo Labeling and Consistency Regularization. - Baoxuan Zhao; Changming Cheng; Shangyu Zhao; Zhike Peng (IEEE Trans. Instrum. Meas., 2023)

A Scalable Gaussian Process for Large-Scale Periodic Data. - Yongxiang Li; Yuting Pu; Changming Cheng; Qian Xiao 003 (Technometrics, 2023)

Adaptive incremental diagnosis model for intelligent fault diagnosis with dynamic weight correction. - Kui Hu; Qingbo He; Changming Cheng; Zhike Peng (Reliab. Eng. Syst. Saf., 2024)

Hierarchical pseudo-label co-calibration with prototypical decision boundary optimization for mechanical fault diagnosis in label-scarce scenarios. - Xinyu Li; Changming Cheng; Zhike Peng (Adv. Eng. Informatics, 2025)

Dynamic domain adaptive ensemble for intelligent fault diagnosis of machinery. - Kui Hu; Qingbo He; Hao Xu; Changming Cheng; Zhike Peng (Knowl. Based Syst., 2025)

Label-guided contrastive learning with weighted pseudo-labeling: A novel mechanical fault diagnosis method with insufficient annotated data. - Xinyu Li; Changming Cheng; Zhike Peng (Reliab. Eng. Syst. Saf., 2025)

Frequency-Assisted Contrastive Learning With Cyclic Fine-Tuning for Rotating Machinery Fault Diagnosis Under Limited Labeled Data. - Xinyu Li; Changming Cheng; Zhike Peng (IEEE Trans. Instrum. Meas., 2025)