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- Yan Xu, Xiaoqin Zeng, Shuiming Zhong
- Neural Computation
- 2013

The purpose of supervised learning with temporal encoding for spiking neurons is to make the neurons emit a specific spike train encoded by the precise firing times of spikes. If only running time is considered, the supervised learning for a spiking neuron is equivalent to distinguishing the times of desired output spikes and the other time during the… (More)

- Jing Yang, Xiaoqin Zeng, Shuiming Zhong, Shengli Wu
- IEEE Transactions on Neural Networks and Learning…
- 2013

This paper, with an aim at improving neural networks' generalization performance, proposes an effective neural network ensemble approach with two novel ideas. One is to apply neural networks' output sensitivity as a measure to evaluate neural networks' output diversity at the inputs near training samples so as to be able to select diverse individuals from a… (More)

- Yu Xue, Shuiming Zhong, Yi Zhuang, Bin Xu
- Applied Mathematics and Computation
- 2014

- Shuiming Zhong, Xiaoqin Zeng, Shengli Wu, Lixin Han
- IEEE Transactions on Neural Networks and Learning…
- 2012

This paper proposes a set of adaptive learning rules for binary feedforward neural networks (BFNNs) by means of the sensitivity measure that is established to investigate the effect of a BFNN's weight variation on its output. The rules are based on three basic adaptive learning principles: the benefit principle, the minimal disturbance principle, and the… (More)

An improved fuzzy c-means algorithm is put forward and applied to deal with meteorological data on top of the traditional fuzzy c-means algorithm. The proposed algorithm improves the classical fuzzy c-means algorithm (FCM) by adopting a novel strategy for selecting the initial cluster centers, to solve the problem that the traditional fuzzy c-means (FCM)… (More)

- Yu Xue, Xiangmao Chang, Shuiming Zhong, Yi Zhuang
- IEEE Trans. Consumer Electronics
- 2014

- Shuiming Zhong, Xiaoqin Zeng, Huiyi Liu, Yan Xu
- Science China Information Sciences
- 2010

The computation of the sensitivity of a Madaline’s output to its parameter perturbation is systematically discussed. Firstly, according to the discrete feature of Adalines, a method based on discrete stochastic technique is proposed, which derives some analytical formulas for the computation of Adalines’ sensitivity. The method can theoretically solve some… (More)

- Xiaoqin Zeng, Jing Shao, Yingfeng Wang, Shuiming Zhong
- Neural Computing and Applications
- 2008

Architecture design is a very important issue in neural network research. One popular way to find proper size of a network is to prune an oversize trained network to a smaller one while keeping established performance. This paper presents a sensitivity-based approach to prune hidden Adalines from a Madaline with causing as little as possible performance… (More)

- Lihong Huang, Xiaoqin Zeng, Shuiming Zhong, Lixin Han
- Neurocomputing
- 2014

- Jing Yang, Xiaoqin Zeng, Shuiming Zhong
- Neurocomputing
- 2013