在无噪声的外部环境中动物的辨别和识别的限制

J. L. Stewart
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引用次数: 2

摘要

分析了感觉细胞分别对应于一个贴片和一个线阵列的一维和二维感觉机制。一个基本的神经脉冲平均率的刺激转换定律被用来解释心理物理学中的一些现象。一种神经噪声理论被发展出来,它被证明可以说明动物辨别的限制,并解释某些观察到的神经机制。最后,采用最佳检测的概念来指定受不可避免的神经噪声约束的理想动物识别感觉图式。实际的动物机制似乎遵循理想。格式塔心理学的某些方面也得到了证明。一般理论为人工动物识别和信息处理系统提供了定量的见解,并指出了机械装置的能力可以达到或超过其生活对等物的程度。为实现理想的人工动物系统提供了明确的设计考虑。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Limits to Animal Discrimination and Recognition in a Noise-Free External Environment
One and two dimensional sensory mechanisms, corresponding to one patch and a line array, respectively, of sensory cells are analyzed. A fundamental stimulus conversion law to average neural pulse rate is employed to explain several phenomena in psychophysics. A theory for neural noise is developed which is shown to specify the limits to animal discrimination and to explain certain observed neural mechanisms. Finally, concepts of optimum detection are employed to specify the ideal animal recognition sensory schema as limited by constraints associated with unavoidable neural noise. Actual animal mechanisms appear to follow the ideal. Certain aspects of Gestalt psychology are also evidenced. The general theory provides quantitative insight into artificial animal recognition and information handling systems and indicates the extent to which the capability of a mechanical device can equal or exceed that of its living counterpart. Explicit design considerations for implementation of the ideal artificial animal system are provided.
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