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.