脑信息特征的评价分类方法

对脑信息处理的能力特征量和总体偏离度特征量进行了确定性评价分类.在分类数上,提出了common分类法,以一般人的特征作为分类基准,在common两边展开,以确定分类数.在分类边界上,提出了根据特征量的正态分布确定分类边界的方法.若特征量分布不是正态分布,则采用了博克斯和考克斯变换将其变为正态分布,最终得到能力特征量和总体偏离度特征量的分类规则.由于人的行为是脑信息处理在宏观上的表现,所以其研究成果可直接用来评价人的能力和行为特征.

Evaluation Approaches of Brain Information Processing Features

A certainty evaluation on ability feature and total deviation index feature of brain information processing is presented. The common approach is presented to gain the classification. It regards the characteristics of common human as the benchmark of classifying, expanding on both sides of common. For finding classification boundary, every feature's distribution function is estimated first, if the function is normal distribution, then the boundary can be computed by the feature's distribution. If it is not normal distribution, the distribution function can be converted into normal distribution by data transform. By the method, classification rules of ability feature and total deviation index feature are proposed. Because human behavior is the macroscopic indirect presentation of brain information processing, the result of this research may be used to evaluate the ability and character of human.