Feng Zhou

According to our database, Feng Zhou authored at least 19 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

IRCNN: A novel signal decomposition approach based on iterative residue convolutional neural network.

Feng Zhou, Antonio Cicone, Haomin Zhou

Pattern Recognit., 2024

2023

Automatic feature learning model combining functional connectivity network and graph regularization for depression detection.

Lijun Yang, Xiaoge Wei, Fengrui Liu, Xiangru Zhu, Feng Zhou

Biomed. Signal Process. Control., April, 2023

Refinements of Approximation Results of Conditional Restricted Boltzmann Machines.

Linyan Gu, Lihua Yang, Feng Zhou

IEEE Trans. Neural Networks Learn. Syst., March, 2023

T2V_TF: An adaptive timing encoding mechanism based Transformer with multi-source heterogeneous information fusion for portfolio management: A case of the Chinese A50 stocks.

Feng Zhou, Qun Zhang, Yuan Zhu, Tian Li

Expert Syst. Appl., 2023

RRCNN⁺: An Enhanced Residual Recursive Convolutional Neural Network for Non-stationary Signal Decomposition.

Feng Zhou, Antonio Cicone, Haomin Zhou

CoRR, 2023

RRCNN: A novel signal decomposition approach based on recurrent residue convolutional neural network.

Feng Zhou, Antonio Cicone, Haomin Zhou

CoRR, 2023

2022

Approximation properties of Gaussian-binary restricted Boltzmann machines and Gaussian-binary deep belief networks.

Linyan Gu, Lihua Yang, Feng Zhou

Neural Networks, 2022

Intraday and interday features in the high-frequency data: Pre- and post-Crisis evidence in China's stock market.

Qun Zhang, Peihui Zhang, Feng Zhou

Expert Syst. Appl., 2022

2021

Attention enhanced long short-term memory network with multi-source heterogeneous information fusion: An application to BGI Genomics.

Qun Zhang, Lijun Yang, Feng Zhou

Inf. Sci., 2021

IF2CNN: Towards non-stationary time series feature extraction by integrating iterative filtering and convolutional neural networks.

Feng Zhou, Haomin Zhou, Zhihua Yang, Linyan Gu

Expert Syst. Appl., 2021

2020

A new prediction method for recommendation system based on sampling reconstruction of signal on graph.

Zhihua Yang, Feng Zhou, Lihua Yang, Qian Zhang

Expert Syst. Appl., 2020

A New Illumination-Rotation-Invariance Texture Feature Based on Quasi-Periodic Signal Analysis.

Zhihua Yang, Qian Zhang, Feng Zhou

IEEE Access, 2020

Segmentation of Pulmonary Nodules Using a GMM Fuzzy C-Means Algorithm.

Xiangxia Li, Bin Li, Fang Liu, Hua Yin, Feng Zhou

IEEE Access, 2020

A New Credit Scoring Model Based on Prediction of Signal on Graph.

Zhihua Yang, Qian Zhang, Feng Zhou, Lihua Yang

Proceedings of the Pattern Recognition and Artificial Intelligence, 2020

2019

A 2-Stage Strategy for Non-Stationary Signal Prediction and Recovery Using Iterative Filtering and Neural Network.

Feng Zhou, Haomin Zhou, Zhihua Yang, Lihua Yang

J. Comput. Sci. Technol., 2019

EMD2FNN: A strategy combining empirical mode decomposition and factorization machine based neural network for stock market trend prediction.

Feng Zhou, Haomin Zhou, Zhihua Yang, Lihua Yang

Expert Syst. Appl., 2019

Cascading logistic regression onto gradient boosted decision trees for forecasting and trading stock indices.

Feng Zhou, Qun Zhang, Didier Sornette, Liu Jiang

Appl. Soft Comput., 2019

2018

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

Zhihua Yang, Qian Zhang, Feng Zhou, Lihua Yang

Digit. Signal Process., 2018

2016

Optimal averages for nonlinear signal decompositions - Another alternative for empirical mode decomposition.

Feng Zhou, Lijun Yang, Haomin Zhou, Lihua Yang

Signal Process., 2016