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A Novel Solid Neuron-Network Chip Based on Both Biological and Artificial Neural Network Theories

机译:一种基于生物和人工神经网络理论的新型固体神经元网络芯片

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Built on the theories of biological neural network, artificial neural network methods have shown many significant advantages. However, the memory space in an artificial neural chip for storing all connection weights of the neuron-units is extremely large and it increases exponentially with the number of neuron-dentrites. Those result in high complexity for design of the algorithms and hardware. In this paper, we propose a novel solid neuron-network chip based on both biological and artificial neural network theories, combining semiconductor integrated circuits and biological neurons together on a single silicon wafer for signal processing. With a neuro-electronic interaction structure, the chip has exhibited more intelligent capabilities for fuzzy control, speech or pattern recognition as compared with conventional ways.
机译:基于生物神经网络理论,人工神经网络方法显示出许多显着的优势。然而,用于存储神经元单元的所有连接重量的人工神经芯片中的存储空间非常大,并且随着神经牙齿的数量呈指数增加。这些导致算法和硬件设计的高复杂性。在本文中,我们提出了一种基于生物和人工神经网络理论的新型固体神经元网络芯片,将半导体集成电路和生物神经元组合在一起在单一硅晶片上以进行信号处理。利用神经电子交互结构,与传统方式相比,该芯片表现出更智能的模糊控制,语音或模式识别的能力。

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