Two completeness theorems set - valued stochastic analysis 集值隨機(jī)分析中的兩個(gè)完備性定理
An algebraic proof of completeness theorem of first - order logic 一階邏輯完備性定理的代數(shù)證明
This paper discusses the system mpm and mfm , constructs the normal form theories of mpm and its tableau system . the soundness and completeness theorem of the tableau system are also given 本文建立了mp ~ m系統(tǒng)的范式理論,構(gòu)造了其表推演系統(tǒng),并證明了其可靠性和完備性。
In this thesis , the author just discusses horn clause sets , and gives how to transform horn clause set into neural network . go a step further , the author discusses how to get the learning algorithm of neural network that is equivalence with resolution principle , and proves completeness theorem and soundness theorem of the algorithm for resolution 本文將所討論的子句集限制在horn子句集上,給出了horn子句集轉(zhuǎn)化為一個(gè)神經(jīng)網(wǎng)絡(luò)模型的方法,進(jìn)j一步,對如何構(gòu)造該神經(jīng)網(wǎng)絡(luò)的學(xué)習(xí)算法來體現(xiàn)歸結(jié)過程進(jìn)行了討論,并證明了此學(xué)習(xí)算法用于歸結(jié)原理的可靠性和完備性。