1) points-set growing
点集扩张
1.
Two numerical algorithms for the new model were described: region merging algorithm and points-set growing algorithm.
对应用于图像处理中的二维Mumford Shah泛函进行简化和降维处理,建立适合于数字信号去噪处理的一维Mumford Shah泛函,利用能量最小化原理的变分方法导出一个新的去噪处理模型,并提出两种不同的计算算法:区域合并算法和点集扩张算法。
2) set_valued extension
集值扩张
3) a point extension
一点扩张
1.
These problems are:the classes of the extensions of the underlying sets,the products of the extensions of the underlying sets,standard extensions of the underlying sets and a point extensions,and got some important results respectively which may be used for some classes of algebras.
就有关基础集扩张的几个问题进行一些必要的讨论,主要有基础集扩张类、基础集扩张的积、基础集标准扩张及一点扩张,分别得到了一些重要的结果,且可应用于各类具体的代
5) node expansion
点扩张
1.
Using the concept of node expansion,the generalized hypercube circulants(GHC)to serve as interconnection network topologies are presented,which contain the wellknown cubeconnected cycles(CCC),and it is shown that the GHC is a Cayley graph.
通过广义超立方体的一种点扩张方法构造了广义超立方体循环网络,它包括了人们熟悉的带环连通立方体;证明了广义超立方体循环网络是Cayley图。
6) setvalued nonexpansive
集值非扩张
1.
Convergence iteration of fixed points of setvalued nonexpansive mapping;
集值非扩张映象不动点迭代收敛性
补充资料:极大扩张和极小扩张
极大扩张和极小扩张
maximal and minimal extensions
极大扩张和极小扩张匡.习的司出目.公油抽lex妇心.旧;MaKcl.Ma刀‘.oe H Mll.”M田.妇oe PaC山一Pe皿朋] 一个对称算子(s笋nr贺苗c opemtor)A的极大扩张和极小扩张分别是算子牙(A的闭包,(见闭算子(cfo“月。详mtor”)和A’(A的伴随,见伴随算子(呐。int opera.tor)).A的所有闭对称扩张都出现在它们之间.极大扩张和极小扩张相等等价于A的自伴性(见自伴算子(义休.adjoint operator)),并且是自伴扩张唯一性的必要和充分条件.A.H.J’Ior朋oB,B.c.lll户、MaR撰
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