Video time encoding machines.
Video time encoding machines.
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DOI：
10.1109/tnn.2010.2103323
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发表时间：
2011-03
影响因子：
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通讯作者：
Pnevmatikakis EA
中科院分区：
文献类型：
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作者：
Lazar AA;Pnevmatikakis EA
我们研究了对自然和合成视频流(电影、动画)等视觉刺激进行时间编码和时间解码的体系结构。时间编码的体系结构类似于早期视觉系统的模型。它由一组与单输入多输出神经电路级联的滤波器组成。神经元放电要么基于阈值激发，要么基于具有反馈的整合激发尖峰机制。我们表明，模拟信息由神经电路表示为由尖峰序列确定的一组带限函数上的投影。在奈奎斯特类型和帧条件下，可以以任意精度从这些投影中恢复编码信号。对于视频时间编码机的体系结构，我们证明了有限能量的带限视频流可以从尖峰序列中忠实地恢复出来，并为完美恢复提供了稳定的算法。恢复的关键条件是种群中的神经元数量高于阈值。
We investigate architectures for time encoding and time decoding of visual stimuli such as natural and synthetic video streams (movies, animation). The architecture for time encoding is akin to models of the early visual system. It consists of a bank of filters in cascade with single-input multi-output neural circuits. Neuron firing is based on either a threshold-and-fire or an integrate-and-fire spiking mechanism with feedback. We show that analog information is represented by the neural circuits as projections on a set of band-limited functions determined by the spike sequence. Under Nyquist-type and frame conditions, the encoded signal can be recovered from these projections with arbitrary precision. For the video time encoding machine architecture, we demonstrate that band-limited video streams of finite energy can be faithfully recovered from the spike trains and provide a stable algorithm for perfect recovery. The key condition for recovery calls for the number of neurons in the population to be above a threshold value.