Implementation and Analysis of Pulse Propagating Networks

脉冲传播网络的实现与分析

• 批准号: 09044183
• 负责人: HORIO Yoshihiko
• 金额: $ 1.79万
• 依托单位: Tokyo Denki University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for international Scientific Research
• 财政年份: 1997
• 资助国家: 日本
• 起止时间: 1997 至 1998
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-09044183/
• 关键词: Brain Modeling; Neural Networks; Real-Number Processing; Analog VLSI; Nonlinear Systems; Dynamical Systems; Neuron Model; Dynamical Cell Assembly; ダイナミカルアセンブリ; 能のモデル; 時空間情報処理; アナログ情報処理; 動的セルアセンブリ

Recent physiological and mathematical studies suggest that the neuron in cortex uses fine time structure of asynchronously incoming excitatoiy action potentials to achieve sophisticated information processing in the brain. Such a neuron functions as a coincident detector among spatio-temporal input pule trains. Continuous variables and time are important in the spatio- temporal network with coincident detector neurons, because real-number processing is possible with them. The real-number processing is very powerful but cannot be realized by the ordinary digital computer.In this research, the spatio-temporal processing network is implemented using analog integrated circuit technology where continuous time and variables such as voltage and current are available, First of all, an asynchronous pulse neuron model that is the core element of the asynchronous pulse propagating network is proposed. The response characteristics of the single neuron and neural network composed of numbers of neurons are investigated. As the results, chaotic responses are observed from single neuron, furthermore, dynamical assembly is organized in the network. The dynamical assembly is one candidate of the information coding in the Spatio- temporal processing. Secondly, analog circuits for the model neuron, the synapse and the axon are proposed. The delay time of the propagating pulses in the axon circuits can be controlled continuously. Moreover, weight of the synaptic circuit can be altered digitally. Finally, the proposed circuits are fabricated using 1.2mum CMOS semiconductor technology. Characteritics of the circuits are measured. As a consequence, chaotic responses are confirmed from the chip. Furthermore, pulse delay in the axon circuit is also observed. The possibility of the real-number processing using asynchronous pulse propagating network is shown through the IC implementation

最近的生理学和数学研究表明，大脑皮层神经元利用非同步传入的兴奋性动作电位的精细时间结构在大脑中实现复杂的信息处理。这种神经元起到时空输入脉冲序列之间的重合检测器的作用。在具有重合检测神经元的时空网络中，连续变量和时间是重要的，因为它们可以进行实数处理。针对传统数字计算机难以实现实数处理的问题，采用模拟集成电路技术实现了具有连续时间和电压、电流等变量的时空处理网络。首先，提出了一种异步脉冲传播网络的核心单元--异步脉冲神经元模型。研究了单个神经元和由多个神经元组成的神经网络的响应特性。结果表明，网络中存在单个神经元的混沌响应，并且网络中存在动态组装。动态拼接是时空处理中信息编码的一种候选方法。其次，提出了模型神经元、突触和轴突的模拟电路。轴突电路中传播脉冲的延迟时间可以连续控制。此外，突触回路的重量可以通过数字方式改变。最后，采用1.2微米的半导体工艺制作了所提出的电路。对电路的特性进行了测量。因此，芯片确认了混沌响应。此外，还观察到轴突电路中的脉冲延迟。通过集成电路的实现，说明了利用异步脉冲传播网络进行实数处理的可能性

项目成果

M.Hangata, Y.Horio and K.Aihara: "Asynchronous pulse neural network model for VLSI implementation" Tech.Rep.IEICE. NLP97-530. 29-35 (1998)

M.Hangata、Y.Horio 和 K.Aihara：“用于 VLSI 实现的异步脉冲神经网络模型”Tech.Rep.IEICE。

M.Hanagata and Y.Horio: "An asynchronous pulse neural network model with finite pulse width for VLSI implementation" Proc.Int.Conf.on Neural Information Processing and Intelligent Information Systems. 1. 26-29 (1997)

M.Hanagata 和 Y.Horio：“用于 VLSI 实现的具有有限脉冲宽度的异步脉冲神经网络模型”Proc.Int.Conf.on 神经信息处理和智能信息系统。

M.Hanagata, Y.Horio and K.Aihara: "Asynchronous pulse neural network model for VLSI implementation" Trans. on Fundamentals, IEICE. E81A, 9. 1853-1859 (1998)

M.Hanagata、Y.Horio 和 K.Aihara：“用于 VLSI 实现的异步脉冲神经网络模型” Trans。

M.Hanagata and Y.Horio: "A modified asynchronous pulse neural network model for VLSI implementation" Proc.Int.Symp.on Nonlinear Theory and Its Applications. 2. 849-852 (1997)

M.Hanagata 和 Y.Horio：“用于 VLSI 实现的改进的异步脉冲神经网络模型”Proc.Int.Symp.on 非线性理论及其应用。

K.Yasuda M.Hanagata R.Kasahara and Y.Horio: "Analog circuit implementation of asynchronous pulse neural network model" Proc.of Int Symp.on Nonlinear Theory and Its Applications. 2. 853-856 (1997)

K.Yasuda M.Hanagata R.Kasahara 和 Y.Horio：“异步脉冲神经网络模型的模拟电路实现”Proc.of Int Symp.on 非线性理论及其应用。