Parallels between the signal processing tasks and biological neurons lead to an understanding of the principles of self-organized optimization of input signal recognition. In the present paper, we discuss such similarities among biological and technical systems. We propose the addition to the well-known STDP synaptic plasticity rule to directs the weight modification towards the state associated with the maximal difference between the background noise and correlated signals. The principle of physically constrained weight growth is used as a basis for such control of the modification of the weights. It is proposed, that biological synaptic straight modification is restricted by the existence and production of bio-chemical 'substances' needed for plasticity development. In this paper, the information about the noise-to-signal ratio is used to control such a substances' production and storage and to drive the neuron's synaptic pressures towards the state with the best signal-to-noise ratio. Several experiments with different input signal regimes are considered to understand the functioning of the proposed approach.
翻译:信号处理任务和生物神经元之间的平行关系导致对输入信号识别自我优化原则的理解。在本文件中,我们讨论了生物和技术系统之间的类似性。我们建议添加众所周知的STDP合成可塑性规则,将重量调整引向与背景噪音和相关信号之间最大差异相关的状态。物理限制重量增长原则被用作控制重量调整的基础。建议生物合成直变受生物化学“物质”的存在和生产的限制,因为这种物质是塑料发展所需的。在本文中,关于噪音对信号比率的信息被用来控制这种物质的生产和储存,用信号对声音的最佳比率将神经神经神经合成压力推向状态。一些使用不同输入信号系统的实验可以理解拟议方法的运作情况。