感知复杂性作为规范化的香农 Entropy
1Department of Psychology, Loyola University Chicago, Chicago, IL 60660, USA.
Entropy (Basel, Switzerland)
|February 26, 2025
概括
这项研究改进了对大脑决策的感知复杂度指标. 我们提出了对复杂性的新定义,解决了当前模型中的局限性,并探索了视觉特征如何相互作用以影响美学判断.
科学领域:
- 神经科学是一个神经科学.
- 认知科学 认知科学
- 信息理论 信息理论
背景情况:
- 感知复杂性对于大脑中的审美决策至关重要.
- 现有的定义,如规范化的香农透,具有理论上的限制.
- 了解复杂性有助于破译美学评估的基础的神经过程.
研究的目的:
- 为了解决对感知复杂性的规范化香农透定义中的理论差距.
- 为视觉复杂性提出精细的定义和计算方法.
- 研究不同视觉变量在复杂性感知中的相互作用.
主要方法:
- 分析测量分辨率对计算的影响.
- 探索空间复杂度计算和理想空间范围的探索.
- 理论建模变量之间的复杂性相互作用,考虑类间相关性和贝叶斯妥协问题.
主要成果:
- 正常化并不能完全纠正对的分辨率效应,尽管影响很小.
- 拟议的替代复杂性定义解决了剩余解决问题的问题.
- 为计算空间复杂性确定了一个最佳的,小的空间范围.
- 感知空间复杂性似乎依赖于翻译同位数.
- 视觉复杂性之间的非线性相互作用很可能是由于类间相关性,但在特定的权重方案下,线性相互作用是可能的.
结论:
- 对感知复杂性的精细定义提供了更好的理论依据.
- 复杂性的空间和变量相互作用方面对理解大脑决策有重大影响.
- 这些理论模型的实验验证是有必要的.
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