Stable indirect adaptive fuzzy-neuro control for a class of nonlinear systems. - Hai-Jun Rong; Guang-She Zhao (FUZZ-IEEE, 2010)

Extended sequential adaptive fuzzy inference system for classification problems. - Hai-Jun Rong; N. Sundararajan 001; Guang-Bin Huang; Guang-She Zhao (Evol. Syst., 2011)

Stable indirect adaptive neural controller for a class of nonlinear system. - Hai-Jun Rong; Suresh Sundaram 002; Guang-She Zhao (Neurocomputing, 2011)

Online learning with kernels in classification and regression. - Guoqi Li; Guangshe Zhao (EAIS, 2012)

Direct adaptive neural control of nonlinear systems with extreme learning machine. - Hai-Jun Rong; Guang-She Zhao (Neural Comput. Appl., 2013)

Model Reference Adaptive Neural Control for nonlinear systems based on Back-Propagation and Extreme Learning Machine. - Hai-Jun Rong; Rong-Jing Bao; Guang-She Zhao (ISSNIP, 2014)

Adaptive fuzzy control of aircraft wing-rock motion. - Hai-Jun Rong; Sai Han; Guang-She Zhao (Appl. Soft Comput., 2014)

Towards the online learning with Kernels in classification and regression. - Guoqi Li; Guangshe Zhao; Feng Yang 011 (Evol. Syst., 2014)

Aircraft recognition using modular extreme learning machine. - Hai-Jun Rong; Ya-Xin Jia; Guang-She Zhao (Neurocomputing, 2014)

An entropy-based method for estimating demographic trends. - Guang-She Zhao; Yi Xu; Guoqi Li; Zhao-Xu Yang (EAIS, 2015)

Adaptive neural control for a class of MIMO nonlinear systems with extreme learning machine. - Hai-Jun Rong; Jin-Tao Wei; Jian-Ming Bai; Guang-She Zhao; Yong-Qi Liang (Neurocomputing, 2015)

Iterative identification of block-oriented nonlinear systems based on biconvex optimization. - Guoqi Li; Changyun Wen; Wei Xing Zheng 001; Guangshe Zhao (Syst. Control. Lett., 2015)

Adaptive backstepping control for magnetic bearing system via feedforward networks with random hidden nodes. - Zhao-Xu Yang; Guang-She Zhao; Hai-Jun Rong; Jing Yang 014 (Neurocomputing, 2016)

Self-evolving kernel recursive least squares algorithm for control and prediction. - Zhao-Xu Yang; Hai-Jun Rong; Guang-She Zhao; Jing Yang 014 (EAIS, 2017)

Matrix differentiation for capacity region of Gaussian multiple access channels under weighted total power constraint. - Zhao-Xu Yang; Guang-She Zhao; Guoqi Li; Hai-Jun Rong (Ann. des Télécommunications, 2017)

A novel meta-cognitive fuzzy-neural model with backstepping strategy for adaptive control of uncertain nonlinear systems. - Hai-Jun Rong; Zhao-Xu Yang; Pak-Kin Wong 001; Chi-Man Vong; Guang-She Zhao (Neurocomputing, 2017)

Data-Driven Fuzzy Controller Design for Hypersonic Vehicle. - Jian-Ming Bai; Guang-She Zhao; Hai-Jun Rong (HPCC/SmartCity/DSS, 2018)

Leader-Follower Consensus over Directed Networks with Time-varying Nonlinear Multi-agents using Minimum Number of Leaders. - Guangshe Zhao; Leitao Gao; Guoqi Li; Yuming Liu; Jiangshuai Huang; Changyun Wen (ICCA, 2018)

Towards the minimum-cost control of target nodes in directed networks with linear dynamics. - Leitao Gao; Guangshe Zhao; Guoqi Li; Lei Deng 003; Fei Zeng (J. Frankl. Inst., 2018)

Seeker-Azimuth Determination with Gyro Rotor and Optoelectronic Sensors. - Jian-Ming Bai; Guangshe Zhao; Hai-Jun Rong; Xianhua Wang (Sensors, 2018)

Lossless Compression for 3DCNNs Based on Tensor Train Decomposition. - Dingheng Wang; Guangshe Zhao; Guoqi Li; Lei Deng 003; Yang Wu 001 (CoRR, 2019)

Kronecker CP Decomposition with Fast Multiplication for Compressing RNNs. - Dingheng Wang; Bijiao Wu; Guangshe Zhao; Hengnu Chen; Lei Deng 003; Tianyi Yan; Guoqi Li (CoRR, 2020)

Novel direct remaining useful life estimation of aero-engines with randomly assigned hidden nodes. - Jian-Ming Bai; Guang-She Zhao; Hai-Jun Rong (Neural Comput. Appl., 2020)

Rethinking the performance comparison between SNNS and ANNS. - Lei Deng 003; Yujie Wu 002; Xing Hu 001; Ling Liang; Yufei Ding 001; Guoqi Li; Guangshe Zhao; Peng Li 001; Yuan Xie 001 (Neural Networks, 2020)

Compressing 3DCNNs based on tensor train decomposition. - Dingheng Wang; Guangshe Zhao; Guoqi Li; Lei Deng 003; Yang Wu 001 (Neural Networks, 2020)

Hybrid tensor decomposition in neural network compression. - Bijiao Wu; Dingheng Wang; Guangshe Zhao; Lei Deng 003; Guoqi Li (Neural Networks, 2020)

Temporal-wise Attention Spiking Neural Networks for Event Streams Classification. - Man Yao; Huanhuan Gao; Guangshe Zhao; Dingheng Wang; Yihan Lin; Zhao-Xu Yang; Guoqi Li (ICCV, 2021)

QTTNet: Quantized tensor train neural networks for 3D object and video recognition. - Donghyun Lee 002; Dingheng Wang; Yukuan Yang; Lei Deng 003; Guangshe Zhao; Guoqi Li (Neural Networks, 2021)

Nonlinear tensor train format for deep neural network compression. - Dingheng Wang; Guangshe Zhao; Hengnu Chen; Zhexian Liu; Lei Deng 003; Guoqi Li (Neural Networks, 2021)

Optimal Target Control of Complex Networks With Selectable Inputs. - Leitao Gao; Guangshe Zhao; Guoqi Li; Fanghong Guo; Fei Zeng (IEEE Trans. Control. Netw. Syst., 2021)

Modeling learnable electrical synapse for high precision spatio-temporal recognition. - Zhenzhi Wu; Zhihong Zhang; Huanhuan Gao; Jun Qin; Rongzhen Zhao; Guangshe Zhao; Guoqi Li (Neural Networks, 2022)

Inherent Redundancy in Spiking Neural Networks. - Man Yao; Jiakui Hu; Guangshe Zhao; Yaoyuan Wang; Ziyang Zhang; Bo Xu 002; Guoqi Li (ICCV, 2023)

Probabilistic Modeling: Proving the Lottery Ticket Hypothesis in Spiking Neural Network. - Man Yao; Yuhong Chou; Guangshe Zhao; Xiawu Zheng; Yonghong Tian 001; Bo Xu 002; Guoqi Li (CoRR, 2023)

Kronecker CP Decomposition With Fast Multiplication for Compressing RNNs. - Dingheng Wang; Bijiao Wu; Guangshe Zhao; Man Yao; Hengnu Chen; Lei Deng 003; Tianyi Yan; Guoqi Li (IEEE Trans. Neural Networks Learn. Syst., 2023)

Attention Spiking Neural Networks. - Man Yao; Guangshe Zhao; Hengyu Zhang 001; Yifan Hu; Lei Deng 003; Yonghong Tian 001; Bo Xu 002; Guoqi Li (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Sparser spiking activity can be better: Feature Refine-and-Mask spiking neural network for event-based visual recognition. - Man Yao; Hengyu Zhang 001; Guangshe Zhao; Xiyu Zhang; Dingheng Wang; Gang Cao; Guoqi Li (Neural Networks, 2023)