Rate–distortion theory and human perception
Rate–distortion theory and human perception
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率失真理论和人类感知
DOI：
10.1016/j.cognition.2016.03.020
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发表时间：
2016
期刊：
影响因子：
3.4
通讯作者：
C. Sims
中科院分区：
文献类型：
--
作者：
C. Sims
知觉的根本目的是帮助实现行为目标。这需要从噪声和不确定的感觉信号中提取和交流有用的信息。同时，考虑到感官信息的复杂性和生物信息处理的局限性，在感知行为中有必要对某些信息进行丢失或丢弃。在这种情况下，什么构成了“最佳”感知系统？本文将率失真理论的数学框架描述为在通信或传输信息的能力受到强烈约束的情况下最小化感知误差成本问题的最优解决方案。率失真理论为开发计算水平的人类知觉模型提供了一个一般的和原则性的理论框架(Marr，1982)。在这个框架下开发的模型能够对人类知觉表现做出定量准确的解释，同时对知觉的性质和目标产生新的见解。本文展示了率失真理论在人类感知中容量限制特别突出的两个基准领域的应用：刺激的离散分类(也称为绝对识别)和视觉工作记忆。本文描述了一个用R统计程序设计语言编写的辅助开发基于率失真理论的模型的软件包。
The fundamental goal of perception is to aid in the achievement of behavioral objectives. This requires extracting and communicating useful information from noisy and uncertain sensory signals. At the same time, given the complexity of sensory information and the limitations of biological information processing, it is necessary that some information must be lost or discarded in the act of perception. Under these circumstances, what constitutes an ‘optimal’ perceptual system? This paper describes the mathematical framework of rate–distortion theory as the optimal solution to the problem of minimizing the costs of perceptual error subject to strong constraints on the ability to communicate or transmit information. Rate–distortion theory offers a general and principled theoretical framework for developing computational-level models of human perception (Marr, 1982). Models developed in this framework are capable of producing quantitatively precise explanations for human perceptual performance, while yielding new insights regarding the nature and goals of perception. This paper demonstrates the application of rate–distortion theory to two benchmark domains where capacity limits are especially salient in human perception: discrete categorization of stimuli (also known as absolute identification) and visual working memory. A software package written for the R statistical programming language is described that aids in the development of models based on rate–distortion theory.
影响因子：
5.4
作者：
Sims, Chris R.;Jacobs, Robert A.;Knill, David C.
通讯作者：
Knill, David C.
影响因子：
5.4
作者：
SHIFFRIN, RM;NOSOFSKY, RM
通讯作者：
NOSOFSKY, RM
影响因子：
5.4
作者：
van den Berg R;Awh E;Ma WJ
通讯作者：
Ma WJ