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ORCIDFeng Zhou 0018
- > Home > Persons > Feng Zhou 0018
Publications
- 2024
[j19]Feng Zhou
, Antonio Cicone, Haomin Zhou:
IRCNN: A novel signal decomposition approach based on iterative residue convolutional neural network. Pattern Recognit. 155: 110670 (2024)- 2023
- [j18]Lijun Yang, Xiaoge Wei, Fengrui Liu, Xiangru Zhu, Feng Zhou:
Automatic feature learning model combining functional connectivity network and graph regularization for depression detection. Biomed. Signal Process. Control. 82: 104520 (2023) - [j16]Linyan Gu, Lihua Yang, Feng Zhou:
Refinements of Approximation Results of Conditional Restricted Boltzmann Machines. IEEE Trans. Neural Networks Learn. Syst. 34(3): 1228-1242 (2023) - [i2]Feng Zhou, Antonio Cicone, Haomin Zhou:
RRCNN: A novel signal decomposition approach based on recurrent residue convolutional neural network. CoRR abs/2307.01725 (2023) - [i1]Feng Zhou, Antonio Cicone, Haomin Zhou:
RRCNN+: An Enhanced Residual Recursive Convolutional Neural Network for Non-stationary Signal Decomposition. CoRR abs/2309.04782 (2023) - 2022
- [j15]Feng Zhou, Huafei Li, Lihua Yang, Zhihua Yang, Linyan Gu:
A novel image deblocking approach within a graph framework. Digit. Signal Process. 120: 103270 (2022) - [j14]Qun Zhang, Peihui Zhang, Feng Zhou:
Intraday and interday features in the high-frequency data: Pre- and post-Crisis evidence in China's stock market. Expert Syst. Appl. 209: 118321 (2022) - [j13]Linyan Gu, Lihua Yang, Feng Zhou:
Approximation properties of Gaussian-binary restricted Boltzmann machines and Gaussian-binary deep belief networks. Neural Networks 153: 49-63 (2022) - 2021
- [j12]Feng Zhou, Haomin Zhou, Zhihua Yang, Linyan Gu:
IF2CNN: Towards non-stationary time series feature extraction by integrating iterative filtering and convolutional neural networks. Expert Syst. Appl. 170: 114527 (2021) - [j11]Qun Zhang, Lijun Yang, Feng Zhou:
Attention enhanced long short-term memory network with multi-source heterogeneous information fusion: An application to BGI Genomics. Inf. Sci. 553: 305-330 (2021) - 2020
- [j10]Zhihua Yang, Qian Zhang, Feng Zhou:
A New Illumination-Rotation-Invariance Texture Feature Based on Quasi-Periodic Signal Analysis. IEEE Access 8: 29901-29911 (2020) - [j8]Zhihua Yang, Feng Zhou, Lihua Yang, Qian Zhang:
A new prediction method for recommendation system based on sampling reconstruction of signal on graph. Expert Syst. Appl. 159: 113587 (2020) - [j7]Linyan Gu, Feng Zhou, Lihua Yang:
Towards the representational power of restricted Boltzmann machines. Neurocomputing 415: 358-367 (2020) - [c1]Zhihua Yang, Qian Zhang, Feng Zhou, Lihua Yang:
A New Credit Scoring Model Based on Prediction of Signal on Graph. ICPRAI 2020: 228-237 - 2019
- [j6]Feng Zhou, Qun Zhang, Didier Sornette, Liu Jiang:
Cascading logistic regression onto gradient boosted decision trees for forecasting and trading stock indices. Appl. Soft Comput. 84 (2019) - [j5]Feng Zhou, Haomin Zhou, Zhihua Yang, Lihua Yang:
EMD2FNN: A strategy combining empirical mode decomposition and factorization machine based neural network for stock market trend prediction. Expert Syst. Appl. 115: 136-151 (2019) - [j4]Feng Zhou, Haomin Zhou, Zhihua Yang, Lihua Yang:
A 2-Stage Strategy for Non-Stationary Signal Prediction and Recovery Using Iterative Filtering and Neural Network. J. Comput. Sci. Technol. 34(2): 318-338 (2019) - 2018
- [j3]Zhihua Yang, Qian Zhang, Feng Zhou, Lihua Yang:
Hilbert spectrum analysis of piecewise stationary signals and its application to texture classification. Digit. Signal Process. 82: 1-10 (2018) - 2016
- [j2]Feng Zhou, Lijun Yang, Haomin Zhou, Lihua Yang:
Optimal averages for nonlinear signal decompositions - Another alternative for empirical mode decomposition. Signal Process. 121: 17-29 (2016) - 2014
- [j1]Lijun Yang, Zhihua Yang, Feng Zhou, Lihua Yang:
A novel envelope model based on convex constrained optimization. Digit. Signal Process. 29: 138-146 (2014)
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