仿生模式识别(拓扑模式识别)——一种模式识别新模型的理论与应用

本文提出了一种模式识别理论的新模型,它是基于"认识"事物而不是基于"区分"事物为目的.与传统以"最佳划分"为目标的统计模式识别相比,它更接近于人类"认识"事物的特性,故称为"仿生模式识别".它的数学方法在于研究特征空间中样本集合的拓扑性质,故亦称作"拓扑模式识别"."拓扑模式识别"的理论基点在于它确认了特征空间中同类样本的连续性(不能分裂成两个彼此不邻接的部分)特性.文中用"仿生模式识别"理论及其"高维空间复杂几何形体覆盖神经网络"识别方法,对地平面刚体目标全方位识别问题作了实验.对各种形状相像的动物及车辆模型作全方位8800次识别,结果正确识别率为99.75%,错误识别率与拒识率分别为0与0.25%.

Bionic (Topological) Pattern Recognition—— A New Model of Pattern Recognition Theory and Its Applications

A new model of pattern recognition principles,witch is based on "matter cognition"instead of "matter classification"in traditional statistical pattern recognition,has been proposed.This new model is better closer to the function of human being,rather than traditional statistical pattern recognition using"optimal seperating"as its main principle.So the new model of pattern recognition is called the Bionic Pattern Recognition.Its mathematical basis are topological analysis of sample set in the high dimensional feature space,therefore it is also called the Topological Pattern Recognition.The basic idea of this model is based on the fact of the continuity in the feature space of any one of the certain kinds of samples.We did experiments on recognition of omnidirectionally oriented rigid objects on the same level,with the Bionic Pattern Recognition using neural networks,which acts by the method of covering the high dimensional geometrical distribution of the sample set in the feature space.Many animal and vehicle models(even with rather similar shapes) were recognized omnidirectionally thousands of times.For total 8800 tests,the correct recognition rate is 99.75%,the error rate and the rejection rate are 0 and 0.25 respectively.