有限动态元胞自动机识别有界对象的复杂性研究
On the Cell-based Complexity of Recognition of Bounded Configurations by Finite Dynamic Cellular Automata
摘要：
本文研究了传统元胞自动机（CA）的推广--有限动态元胞自动机（FDCA）识别一类有界构形的复杂性。受基于CA的生物和计算机视觉模型的启发，本研究试图推导出一个复杂性度量的属性和输入配置的类别，使其有利于实现识别通过一个两层的自动机相比，一个一层的自动机。一个图像模式识别任务的形式化模型被用来证明导出的条件可以满足一个非空的实际问题集。
英文摘要：
This paper studies complexity of recognition of classes of bounded configurations by a generalization of conventional cellular automata (CA) -- finite dynamic cellular automata (FDCA). Inspired by the CA-based models of biological and computer vision, this study attempts to derive the properties of a complexity measure and of the classes of input configurations that make it beneficial to realize the recognition via a two-layered automaton as compared to a one-layered automaton. A formalized model of an image pattern recognition task is utilized to demonstrate that the derived conditions can be satisfied for a non-empty set of practical problems.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
