By YuXi Liu, ZhiFeng Zhang (auth.), De-Shuang Huang, Yong Gan, Prashan Premaratne, Kyungsook Han (eds.)
The three-volume set LNCS 6838, LNAI 6839, and LNBI 6840 constitutes the completely refereed post-conference lawsuits of the seventh foreign convention on clever Computing, ICIC 2011, held in Zhengzhou, China, in August 2011. This quantity comprises ninety three revised complete papers, from a complete of 281 shows on the convention - rigorously reviewed and chosen from 832 preliminary submissions. The papers deal with all concerns in complex clever Computing, specially Methodologies and functions, together with theories, methodologies, and purposes in technological know-how and expertise. They contain more than a few strategies reminiscent of man made intelligence, trend popularity, evolutionary computing, informatics theories and purposes, computational neuroscience and bioscience, delicate computing, human desktop interface matters, etc.
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Extra resources for Bio-Inspired Computing and Applications: 7th International Conference on Intelligent Computing, ICIC 2011, Zhengzhou,China, August 11-14. 2011, Revised Selected Papers
Mathematics and Computers in Simulation 74, 38–46 (2007) 3. : Delay-dependent robust exponential stability for uncertain recurrent neural networks with time-varying delays. International Journal of Neural Systems 17, 207–218 (2007) 4. : Robust stability of discrete-time stochastic neural networks with time-varying delays. Neurocomputing 71, 823–833 (2008) 5. : Stability analysis of discrete-time stochastic neural networks with time-varying delay. Neurocomputing. 773, 740-748 (2010) 6. : Robust stability nanlysis of discretetime stochastic neural networks with time-varying delays.
1, is proposed to simulate such visual attention. Suppose that a visual image is presented to the retina and an edge firing rate map  is obtained as the input for the network. The line detection layer contains two pathways. The horizontal pathway contains a neuron array Nh with the same size as the input neuron array. Each neuron has a receptive field corresponding to a horizontal synapse strength matrix Wh. The vertical pathway contains a neuron array Nv with the same size as input neuron array.
Cn Abstract. This paper proposes a novel partially connected neural evolutionary model (Parcone) architecture to simulate the relationship of stock and technical indicators to predict the stock price index. Different from artificial neural networks, the architecture has corrected three drawbacks: (1) connection between neurons of is random; (2) there can be more than one hidden layer; (3) evolutionary algorithm is employed to improve the learning algorithm and train weights. The more hidden knowledge stored within the historic time series data are needed in order to improve expressive ability of network.