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Visual data Processing and Action Control Using Binary Neural Network

机译:使用二进制神经网络进行视觉数据处理和动作控制

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A new model of the brain-like neural network for visual data processing and action control is proposed. The neural network is built on discrete elements with binary input and output with memory cells. Optimization of the network is conducted using a natural selection process within the framework of an artificial life paradigm. The theoretical principles of the neuron and network structure construction have been tested and assured by real experiment using a computer program which models a population of virtual bacteria living and evolving in a restricted 2D area. Virtual bacteria act using binary visual information as input. Given the rules of survival and neural network mutation, new generations of bacteria form their brain using the neural networks of their successful predecessors. The proposed approach demonstrates the possibility of constructing a brain-like neural network based only on binary data processing.
机译:提出了一种用于视觉数据处理和动作控制的类脑神经网络的新模型。神经网络建立在离散元件上,带有存储单元的二进制输入和输出。网络的优化是在人工生命范式的框架内使用自然选择过程进行的。神经元和网络结构构建的理论原理已经通过使用计算机程序的真实实验进行了测试和保证,该计算机程序对在受限2D区域中生活和进化的虚拟细菌种群进行建模。虚拟细菌使用二进制视觉信息作为输入来起作用。根据生存和神经网络突变的规则,新一代细菌将利用其成功前辈的神经网络来形成它们的大脑。所提出的方法证明了仅基于二进制数据处理构建类似大脑的神经网络的可能性。

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