Advanced Intelligent Computing Theories and Applications. by Xue-Quan Xu, Xian-Bin Wen, Yue-Qing Li, Jin-Juan Quan

By Xue-Quan Xu, Xian-Bin Wen, Yue-Qing Li, Jin-Juan Quan (auth.), De-Shuang Huang, Laurent Heutte, Marco Loog (eds.)

The foreign convention on clever Computing (ICIC) was once shaped to supply an annual discussion board devoted to the rising and difficult issues in man made intelligence, desktop studying, bioinformatics, and computational biology, and so forth. It goals to convey - gether researchers and practitioners from either academia and to percentage principles, difficulties and options relating to the multifaceted points of clever computing. ICIC 2007, held in Qingdao, China, August 21-24, 2007, constituted the 3rd - ternational convention on clever Computing. It outfitted upon the luck of ICIC 2006 and ICIC 2005 held in Kunming and Hefei, China, 2006 and 2005, respectively. This 12 months, the convention focused more often than not at the theories and methodologies in addition to the rising functions of clever computing. Its objective used to be to unify the image of up to date clever computing suggestions as an indispensable idea that highlights the tendencies in complicated computational intelligence and bridges theoretical examine with functions. for this reason, the subject matter for this convention used to be “Advanced clever Computing expertise and Applications”. Papers targeting this subject matter have been solicited, addressing theories, methodologies, and functions in technological know-how and technology.

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Extra resources for Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence: Third International Conference on Intelligent Computing, ICIC 2007, Qingdao, China, August 21-24, 2007. Proceedings

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The host image is decomposed into wavelet domain, then watermark bits embedded in the selected coefficients blocks. In watermark extraction, the original watermark is retrieved by neural network. Acknowledgements This work is supported in part by the National Natural Science Foundation of China (No. 60375003), the Aeronautics and Astronautics Basal Science Foundation of China (No. 03I53059), the Science and Technology Development Foundation of Tianjin Higher-learning (2006BA15). References 1. ,.

3 Iterative Gradient Descent-Based Method with Additive Momentum Put the input and actual value of p samples into the wavelet network and calculate the output values and the system error of the network. The training is base on the minimization of the following cost function: Application Server Aging Prediction Model Based on Wavelet Network E= 1 p ∑ (dl − yl )2 2 l =1 19 (8) where yl is the computing value of the l th sample on the output node in the wavelet network. And dl is the actual value of the output node.

Dark lines show that the corresponding neurons fires with a low frequency and indicate the edges with low contrast. Using the firing rates, different contrast edges can be separated. Fig. 3. Firing rate map from output layer In order to compare with Sobel and Canny edge detection methods, the results for benchmark image Lena photo are shown in Fig. 4. Lena photo Sobel edges Canny edges Neuron firing rate map Fig. 4. Comparison of neuron firing rate map with other edge detecting methods 5 Discussion Spiking neural networks are constructed by a hierarchical structure that is composed of spiking neurons with various receptive fields and plasticity synapses.

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