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Titlebook: Artificial Neural Networks - ICANN 2008; 18th International C Véra K?rková,Roman Neruda,Jan Koutník Conference proceedings 2008 Springer-Ve

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21#
發(fā)表于 2025-3-25 06:15:59 | 只看該作者
Modeling and Synthesis of Computational Efficient Adaptive Neuro-Fuzzy Systems Based on Matlabmodel generates computational-efficient implementations without loss of approximation capabilities or learning performance. The tool has been used to develop both software and hardware approaches as well as special architectures for hybrid hardware/software embedded systems.
22#
發(fā)表于 2025-3-25 09:17:09 | 只看該作者
Embedded Neural Network for Swarm Learning of Physical Robotsre started simultaneously from their randomized initial conditions. The presence of several robots consequently formed a dynamic environment, in which an action of one robot affected the learning process of others. We demonstrated the efficiency of the embedded learning mechanism with respect to different environmental factors.
23#
發(fā)表于 2025-3-25 11:44:09 | 只看該作者
24#
發(fā)表于 2025-3-25 19:06:13 | 只看該作者
25#
發(fā)表于 2025-3-25 22:13:04 | 只看該作者
26#
發(fā)表于 2025-3-26 01:53:32 | 只看該作者
Mimicking Go Experts with Convolutional Neural Networks9% of the moves made in test expert Go games, improving upon the state of the art, and that the best single convolutional neural network of the ensemble achieves 34% accuracy. This network has less than 10. parameters.
27#
發(fā)表于 2025-3-26 05:40:46 | 只看該作者
Conference proceedings 2008ring patterns: from cognition to disease, and constructive neural networks and two workshops new trends in self-organization and optimization of artificial neural networks, and adaptive mechanisms of the perception-action cycle.
28#
發(fā)表于 2025-3-26 08:39:37 | 只看該作者
29#
發(fā)表于 2025-3-26 15:40:48 | 只看該作者
Feng Shui and Traditional Chinese Medicineata mining. The general approach is verified experimentally in the practical problem of detecting intrusions in computer networks. Empirical results prove that the KWM model can effectively support such a difficult classification task and combine unsupervised and supervised.
30#
發(fā)表于 2025-3-26 16:53:47 | 只看該作者
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