1) adjoint operator
伴随算子
1.
On the adjoint operators of regular FI-algebras;
正则FI-代数上的伴随算子
2.
The boundedness,adjoint operator and spectrum of multiplication operators are investigated,the condition for multiplication operators to be positive operators is also presented.
研究了Hilbert空间L2(μ)上的乘法算子,对其有界性,伴随算子以及乘法算子的谱进行了刻画,并给出了乘法算子成为正算子的条件。
3.
The regularity and the adjoint operators of family of fuzzy implication operator L-γ-G were discussed.
讨论了L-λ-G族模糊蕴涵算子的伴随算子及其正则性,指出了在模糊蕴涵算子族L-λ-G中,只有R_(Lu)算子与R_G算子有伴随算子且具有正则性,从而说明了这两种算子是较理想的蕴涵算子。
2) concomitant implication operator
伴随蕴涵算子
1.
Taking advantage of the concomitant implication operator of TG,which is a t-norm,a simple efficient learning algorithm is proposed for the fuzzy Hopfield Networks based on fuzzy composition of Max and TG(Max-TG FHNN).
利用t-模的伴随蕴涵算子,为基于Max和TG合成的Hopfield网络Max-TGFHNN提供了一种新的学习算法,此处TG是Godelt-模算子。
2.
Taking advantage of the concomitant implication operator of T_ L , which is a t-norm, a simple efficient learning algorithm was proposed for the fuzzy bi-directional associative memory based on fuzzy composition of Max and T_ L (Max-T_ L FBAM).
利用t-模的伴随蕴涵算子,为基于Max和TL合成的模糊双向联想记忆网络Max-TLFBAM提供了一种新的学习算法,此处TL是Lukasiewiczt-模算子。
3.
Taking advantage of the concomitant implication operator of Tes,which is a t-norm and was presented by Einstein,a simple efficient learning algorithm is proposed for the fuzzy associative memory based on fuzzy composition of Max and Tes(Max-Tes FAM).
文章利用t-模的伴随蕴涵算子,为基于Max和Tes合成的模糊联想记忆网络Max-TesFAM提供了一种新的学习算法,此处Tes是由爱因斯坦提出的一种t-模算子。
3) discrete adjoint operator method
离散伴随算子法
4) partially adjoint operator
部分伴随算子
5) quasi self adjoint operator
伪自伴随算子
6) adjoint differential operator
伴随微分算子
补充资料：伴随算子
伴随算子
adjoint operator
伴随算子[adj‘nt卿.奴甘;eoop，翎。肠‘ooepaT0p] 一个线性算子A’:Y’~x’(这里x‘与Y’分别是局部凸空间X与y的强对偶)，它由线性算子A:X~y依照下面方式构造而成.设A的定义域几在X中是处处稠密的.如果对所有的x〔D，，有
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参考词条