1) sample recognition
样本判别
2) judgement sample
判断样本
3) specimen discerning
样本识别
1.
This paper combines specimen discerning with the method of analysis hierarchy process and gives a new method——integrated analysis hierarchy process.
本文将样本识别方法与层次分析法相结合 ,提出了综合集成层次分析法 ,可广泛应用于社会经济系统的因素分析和综合评价。
4) fundamental critical form
基本判别式
1.
In this paper, with Siegel-Tatuzawa Theorem we give an upper bound of the fundamental critical form for the quadratic number field whose all ideals areAmbiguous ones.
本文运用Siegel—Tatuzawa定理讨论了任一理想均为Ambiguous理想的二次域Q(d～(1/d))的基本判别式d的上界问题。
5) sample identification rate
样本识别率
1.
In this paper,research on the stability,the convergence tendency of the power value,the sample identification rate of the BP Neural Network and the influence to the power value was made by the Network s general error with a example whose structure of the BP Neural Network is 3-5-2.
以结构为 3- 5 - 2的网络为例 ,对BP神经网络的稳定性、权值的收敛趋势、样本识别率和网络总误差对权值的影响等做了研究 ,结果表明系统总误差的减小会促使网络权值将向最优方向调整 ,但这种调整有一定极限 。
补充资料：里雅普诺夫判别定理
见运动稳定性。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条