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  • 机器学习中使用的神经网络(二)

    什么是神经网络?

    大脑如何工作?

    Each neuron receives inputs from other neurons  每个神经元接收其他神经元的输入
    - A few neurons also connect to receptors.  一些神经元连接到神经末梢
    - Cortical neurons use spikes to communicate.大脑神经元使用突触来通讯
    • The effect of each input line on the neuron is controlled by a synaptic weight

        每行输入神经元的效果都由突触的权值控制

    The weights can be positive or negative. 权值可能是正的也可以是负的
    • The synaptic weights adapt so that the whole network learns to perform useful computations

      突触的权值调整,是整个网络进行有用的计算

    – Recognizing objects, understanding language, making plans,controlling the body.

        识别物体,理解语言,规划,控制身体

    – A huge number of weights can affect the computation in a very short time. Much better bandwidth to stored knowlege than a modern workstation has.
      大量的权值短时间内能够影响计算。

    Modularity and the brain 模块性大脑
    • Different bits of the cortex do different things. 皮层的不同部位做不同的事
    – Local damage to the brain has specific effects.  局部的损伤导致某些特定的影响,比如失去语言能力,不能识别
    – Specific tasks increase the blood flow to specific regions.
    • But the remarkable thing about cortex is looks pretty much the same all over, and that strongly suggests that it's got a fairly flexible universal learning alogrithm on it.
    – Early brain damage makes functions relocate.
    • Cortex is made of general purpose stuff that has the ability to turn into
    special purpose hardware in response to experience.
    – This gives rapid parallel computation plus flexibility.
    – Conventional computers get flexibility by having stored sequential programs, but this requires very fast central processors to perform long sequential computations.

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  • 原文地址:https://www.cnblogs.com/jinee/p/4472536.html
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