- 更多网络例句与拟范数相关的网络例句 [注:此内容来源于网络,仅供参考]
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In chapter 4, we give the definition of quasi-norm of linear operator with respect to a given bounded set in F* space and study some of its properties.
第四章 在F~*空间上给出线性算子关于一个给定有界集的拟范数的定义,研究它的某些性质。
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Thirdly,quasi-normal inequalities of a-variation maximal operator and a-conditional variation maximal operator of scalar predictable tree martingales areidentified by the use of martingale transforms and by the construction of convex or concave function method;on this basis and with the help of previsiblity or regu-larity,Burkholder-Davis-Gundy\'s inequality of a-variation maximal operator and a-conditional variation maximal operator of scalar predictable tree martingales are iden-tified by the application of Hardy-Lorentz interpolation theory.At the same time,bythe use of G.
再次,应用鞅变换和构造凸或凹函数方法证明了标量值可料树鞅的α-方极大算子和α-条件方极大算子的拟范数不等式;然后,在这些拟范数不等式的基础上,应用Hardy-Lorentz空间插值方法证明了当树鞅是可控或正规树鞅时关于标量值可料树鞅α-方极大算子和α-条件方极大算子的Burkholder-Davis-Gundy's不等式成立。
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Pisier\'s results,under tree martingale valued space X is isomorphic toan a-uniformly convex space (2≤a<∞),some quasi-normal or normal inequalitiesof a-variation maximal operator and a-conditional variation maximal operator of X-valued predictable tree martingales are identified.
同时,用G.Pisier's结果在树鞅取值空间X同构于a一致凸Banach空间条件下,证明了几个X-值树鞅α-方极大算子和a-条件方极大算子的拟范数不等式与范数不等式。
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Robust goodness-of-fit test of AP model based on L-1 norm fitting[J].
基于L-1范数拟合的AR模型的稳健的拟合优度检验[J]。
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Robust goodness-of-fit test of AR model based on L-1 norm fitting .
基于L-1范数拟合的AR模型的稳健的拟合优度检验。
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In the first pa.rt,we clolinc the TC inodnhis of convexity and TC modulus of smoothness of quasi-Baiiach space, and prove that the space which is characterized by uniform convexity is same as the space which is cliaracteri/,ed by uniform TC convcxity.Then we give several characterizations of q-uniformly TC convex quasi-Banach space.At the same time ,we prove the triionned-theorcm.In the second part, we give the relationships between some inequalities of martingales with values in quasi-Banach space and uniformly TC convex quasi-Banach space.
本文分四部分,第一部分在拟Banach空间上定义了TC凸性模和TC光滑模并证明了在Banach空间上它分别和一致凸性和一致光滑性刻划的空间是一致的,即Banach空间X是一致TC凸的的充分必要条件是它是一致凸的,Banach空间X是一致TC光滑的充分必要条件是它是一致光滑的,还分别得出了判定一致TC凸和一致TC光滑的几个充分必要条件,同时还证明了在拟范数下的重赋范定理。
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Firstly, through applying Hilbert-Sobolev norm to measure fidelity term, a total variation filter is used to smooth the normal vectors of the level curves of a noise image. And then, a model is constructed to find a surface which fit smoothed normal vectors.
该方法首先引入负指数Hilbert- Sobolev范数度量逼近项,对图像水平曲线的法向量场进行全变差正则化磨光,然后构造出一个曲面拟合模型,拟合磨光后的流场。
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Furthermore, the relationship between the residual norm of the semi-refined approximate eigenpair and that of the approximate refined eigenpair is discussed. The semi-refined biorthogonalization Lanczos algorithm is given. We carry on some numerical experiments, and the results show that the new algorithm is more efficient than its conventional counterpart.
根据精化投影方法的思想,提出了半精化双正交Lanczos方法,建立了半精化特征对和精化特征对对应的残量范数之间的关系,给出了半精化双正交Lanczos算法,数值实验表明,该算法比双正交Lanczos算法和拟精化双正交Lanczos算法优越。
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Moreover, we discuss the relationship between the residual norm of the quasi-refined approximate eigenpair and that of the refined eigenpair, and the quasi-refined biorthogonalization Lanczos algorithm is given. Some numerical experiments are carried on, and the results illustrate that the newalgorithm is superior to the classic one. 2.We propose the semi-refined biorthogonalization Lanczos method which is based on the refined projection idea.
将精化投影方法的思想和拟精化思想相结合,提出了拟精化双正交Lanczos方法,建立了拟精化近似特征对和精化近似特征对对应的残量范数之间的关系,给出了拟精化双正交 Lanczos算法,并进行了数值实验,具体算例表明,该算法比双正交Lanczos算法优越; 2。
- 更多网络解释与拟范数相关的网络解释 [注:此内容来源于网络,仅供参考]
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quasi metric space:拟度量空间
quasi metric 拟度量 | quasi metric space 拟度量空间 | quasi norm 拟范数
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quasi normal family:拟正规族
quasi norm 拟范数 | quasi normal family 拟正规族 | quasi normal vectors 拟正规向量
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pseudonorm:拟范数
拟定义 pseudodefinition | 拟范数 pseudonorm | 拟随机二进序列 pseudorandom binary sequence (P.R.B.S.)
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quasi norm:拟范数
quasi metric space 拟度量空间 | quasi norm 拟范数 | quasi normal family 拟正规族