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By the definition of fractal, the BP network is proved to be a fractal whose fractal dimension ranges from 2.5 to 5. The relationship between generalization and learning rate of the BP network and the relationship between generalization and fractal dimension of weights are researched in this paper. The results present that the generalization of BP network becomes better with the increasing of the...
Multi-class object recognition is a critical capability for an intelligence robot to perceive its environment. In this paper, a new approach consisting of a number of modular neural networks is proposed to recognize multiple classes of objects for a robotic system. The population of the modular neural networks depends on the class number of the objects to be recognized and each modular network only...
Many interesting problems in reinforcement learning (RL) are continuous and/or high dimensional, and in this instance, RL techniques require the use of function approximators for learning value functions and policies. Often, local linear models have been preferred over distributed nonlinear models for function approximation in RL. We suggest that one reason for the difficulties encountered when using...
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