A New Approach for Estimating the Attraction Domain for Hopfield-Type Neural Networks. - Dequan Jin; Jigen Peng (Neural Comput., 2009)

Approximation on attraction domain of Cohen-Grossberg neural networks. - Dequan Jin; Zhili Huang; Jigen Peng (Appl. Math. Comput., 2011)

A New Clustering Approach on the Basis of Dynamical Neural Field. - Dequan Jin; Jigen Peng; Bin Li (Neural Comput., 2011)

Investigation on Amari's dynamical neural field with global constant inhibition. - Dequan Jin; Jigen Peng (Neural Networks, 2015)

Dimension reduction based on small sample entropy learning for hand-writing image. - Murong Yang; Jigen Peng; Ziyan Qin; Penghe Chen; Dequan Jin (Multim. Tools Appl., 2021)

A Novel Neural Model With Lateral Interaction for Learning Tasks. - Dequan Jin; Ziyan Qin; Murong Yang; Penghe Chen (Neural Comput., 2021)

A Weighting Method for Feature Dimension by Semisupervised Learning With Entropy. - Dequan Jin; Murong Yang; Ziyan Qin; Jigen Peng; Shihui Ying (IEEE Trans. Neural Networks Learn. Syst., 2023)

HCNM: Hierarchical cognitive neural model for small-sample image classification. - Dequan Jin; Ruoge Li; Nan Xiang; Di Zhao; Xuanlu Xiang; Shihui Ying (Expert Syst. Appl., 2025)

ViTNF: Leveraging Neural Fields to Boost Vision Transformers in Generalized Category Discovery. - Jiayi Su; Dequan Jin (CoRR, 2025)

RoNFA: Robust Neural Field-based Approach for Few-Shot Image Classification with Noisy Labels. - Nan Xiang; Lifeng Xing; Dequan Jin (CoRR, 2025)