递归相似

RECURSIVE SIMILARITY

为观测研究提出一种动力学模型。新模型将不依赖统计概念，也不依赖对象的任何先验的理论模型，因此它具有极大的一般性。递归相似是核心概念，由此产生邻域函数、跃度和演化相似等概念和可计算的指标，它们描述了观测序列的演化性态。从观测序列（向量的或函数的）重建动力系统是我们的总体工作，本文是这项工作中的独立部分。

This paper is devoted to a dynamic model for observational study,which does notdepend on statistical concept nor on any a priori theoretical model of the object.Consequently,itpocesses great generality.Recursive similarity is the central concept of the research,resultingfrom which are neighborhood function,jumping,evolution similarity and calculable index,responsible for describing the evolution properties of the observational sequence.As a target,thereconstruction of a dynamic system based onan observational(vectorial or functional)series andthe article is only part of the research towards the goal.