目的应用实验室生化酶学测定项目的短期西格玛(Sigmashort-term)估算其保证西格玛SigmaAssured,并依据系统误差功效图得出相应的统计质量控制(statistical quality control,SQC)规则,估计生化酶学测定项目的长期缺陷率(defects per mill...目的应用实验室生化酶学测定项目的短期西格玛(Sigmashort-term)估算其保证西格玛SigmaAssured,并依据系统误差功效图得出相应的统计质量控制(statistical quality control,SQC)规则,估计生化酶学测定项目的长期缺陷率(defects per million,DPM),确保实验室生化酶学测定项目结果的可靠。方法计算公式Sigma=(TEa–Bias)/CV;Sigmalong-term=Sigmashort-term-1.5;SigmaAssured=SigmaObserved–SigmaSQC,SigmaAssured=1.65,SQC规则为13s/22s/R4s/41s/8x,N=2。结果计算得到实验室丙氨酸氨基转移酶(ALT)的Sigmashort-term=3.6,DPM=274253;天门冬氨酸氨基转移酶(AST)的Sigmashort-term=7.9,DPM<3.4;谷氨酰基转移酶(GGT)的Sigmashort-term=5.6,DPM=4661;碱性磷酸酶(ALP)的Sigmashort-term=7.4,DPM=5;淀粉酶(AMY)Sigmashort-term=17.7,DPM<3.4;肌酸激酶(CK)Sigmashort-term=9.3,DPM≤3.4;乳酸脱氢酶(LDH)的Sigmashort-term=6.1,DPM=968;脂肪酶(LPS)的Sigmashort-term=5.3,DPM=10724。结论实验室生化酶学测定项目期望的长期缺陷率在误差检出率(Ped)达到90%,其SigmaAssured在1.65,相同的SQC规则13s/22s/R4s/41s/8x,N=2,的情况下,其Sigma short-term越大,长期DPM越低,才能确保生化酶学测定项目的结果可靠。展开更多
A novel Krein space approach to robust H∞ filtering for linear uncertain systems is developed. The parameter uncertainty, entering into both states and measurement equations, satisfies an energy-type constraint. Then...A novel Krein space approach to robust H∞ filtering for linear uncertain systems is developed. The parameter uncertainty, entering into both states and measurement equations, satisfies an energy-type constraint. Then a Krein space approach is used to tackle the robust H∞ filtering problem. To this end, a new Krein space formal system is designed according to the original sum quadratic constraint （SQC） without introducing any nonzero factors into it and, consequently, the estimate recursion is obtained through the filter gain in Krein space. Finally, a numerical example is given to demonstrate the effectiveness of the proposed approach.展开更多
基金supported by the National Natural Science Foundation of China (51179039)the Ph.D. Programs Foundation of Ministry of Education of China (20102304110021)
文摘A novel Krein space approach to robust H∞ filtering for linear uncertain systems is developed. The parameter uncertainty, entering into both states and measurement equations, satisfies an energy-type constraint. Then a Krein space approach is used to tackle the robust H∞ filtering problem. To this end, a new Krein space formal system is designed according to the original sum quadratic constraint （SQC） without introducing any nonzero factors into it and, consequently, the estimate recursion is obtained through the filter gain in Krein space. Finally, a numerical example is given to demonstrate the effectiveness of the proposed approach.
