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基于特征子阵匹配的织物组织分析 被引量:4
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作者 袁惠芬 王旭 《纺织学报》 EI CAS CSCD 北大核心 2009年第9期45-48,54,共5页
为能在仿制设计过程中快速且简便地提取待分析织物的完全组织循环参数,提出一种基于特征子阵匹配的织物组织分析方法。根据织物分析得到的意匠图,建立相应的组织矩阵。通过一维搜索方法分别找出组织矩阵经、纬向可能的循环,并以此建立... 为能在仿制设计过程中快速且简便地提取待分析织物的完全组织循环参数,提出一种基于特征子阵匹配的织物组织分析方法。根据织物分析得到的意匠图,建立相应的组织矩阵。通过一维搜索方法分别找出组织矩阵经、纬向可能的循环,并以此建立特征子阵。分别对特征子阵进行二维铺设,根据铺设结果和组织矩阵是否匹配,判定特征子阵是否为完全组织。研究表明:分析完全组织循环数大的织物时,一维搜索的方法可以优化特征子阵的寻找和选择;通过对特征子阵的铺设并和原始意匠图的匹配,可以实现完全组织循环参数的提取。 展开更多
关键词 织物组织 组织矩 特征子阵 变换
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宽带子阵域特征空间稳健对角减载波束形成 被引量:1
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作者 王昊 马启明 《电子学报》 EI CAS CSCD 北大核心 2019年第3期584-590,共7页
针对宽带子阵域自适应波束形成器在实际使用中稳健性下降、对弱信号的检测能力受信噪比限制的问题,提出了一种宽带子阵域特征空间稳健对角减载自适应波束形成方法.首先提出利用子阵域特征空间投影法修正导引向量并得到球形不确定集的估... 针对宽带子阵域自适应波束形成器在实际使用中稳健性下降、对弱信号的检测能力受信噪比限制的问题,提出了一种宽带子阵域特征空间稳健对角减载自适应波束形成方法.首先提出利用子阵域特征空间投影法修正导引向量并得到球形不确定集的估计,再利用RCB(Robust Capon Beamformer)算法得到约束条件下的最优权值.另一方面,利用子阵域互谱密度矩阵的最小特征值作为子阵域非相关噪声功率的估计并进行对角减载,以最优权值对减载矩阵波束形成得到子带波束输出,对每个窄子带重复上述处理,再将结果非相干叠加即可得到本文方法的最终结果.理论及实验分析表明方法能提高自适应波束形成器的稳健性及输出信噪比. 展开更多
关键词 信号与信息处理 宽带稳健自适应波束形成 特征空间 对角减载
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Some Remarks for Discrete Versions of Nodal Domain Theorems
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作者 李耀堂 关莉 《Journal of Mathematical Research and Exposition》 CSCD 北大核心 2003年第2期275-278,共4页
In this paper, an error is firstly pointed out in the proof of the main theorems (Theorem 4 and Theorem 6) in [1]. Then the error is corrected and the right proof is given.
关键词 nodal domain theorem discrete version
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ASYMPTOTIC PROPERTY OF THE TIME-DEPENDENT SOLUTION OF A RELIABILITY MODEL 被引量:9
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作者 GeniGupur GUOBaozhu 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2005年第3期319-339,共21页
We discuss a transfer line consisting of a reliable machine, an unreliable machine and a storage buffer. This transfer line can be described by a group of partial differential equations with integral boundary conditio... We discuss a transfer line consisting of a reliable machine, an unreliable machine and a storage buffer. This transfer line can be described by a group of partial differential equations with integral boundary conditions. First we show that the operator corresponding to these equations generates a positive contraction C0-semigroup T(t), and prove that T(t) is a quasi-compact operator. Next we verify that 0 is an eigenvalue of this operator and its adjoint operator with geometric multiplicity one. Last, by using the above results we obtain that the time-dependent solution of these equations converges strongly to their steady-state solution. 展开更多
关键词 C_0-semigroup quasi-compact operator adjoint operator EIGENVALUE
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Review:Global nutrient profiling by Phenotype MicroArrays:a tool complementing genomic and proteomic studies in conidial fungi 被引量:4
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作者 Lea ATANASOVA Irina S.DRUZHININA 《Journal of Zhejiang University-Science B(Biomedicine & Biotechnology)》 SCIE CAS CSCD 2010年第3期151-168,共18页
Conidial fungi or molds and mildews are widely used in modern biotechnology as producers of antibiotics and other secondary metabolites,industrially important enzymes,chemicals and food.They are also important pathoge... Conidial fungi or molds and mildews are widely used in modern biotechnology as producers of antibiotics and other secondary metabolites,industrially important enzymes,chemicals and food.They are also important pathogens of animals including humans and agricultural crops.These various applications and extremely versatile natural phenotypes have led to the constantly growing list of complete genomes which are now available.Functional genomics and proteomics widely exploit the genomic information to study the cell-wide impact of altered genes on the phenotype of an organism and its function.This allows for global analysis of the information flow from DNA to RNA to protein,but it is usually not sufficient for the description of the global phenotype of an organism.More recently,Phenotype MicroArray (PM) technology has been introduced as a tool to characterize the metabolism of a (wild) fungal strain or a mutant.In this article,we review the background of PM applications for fungi and the methodic requirements to obtain reliable results.We also report examples of the versatility of this tool. 展开更多
关键词 Biolog Phenotype MicroArray Mitosporic fungi Carbon metabolism TRICHODERMA ASPERGILLUS BIOTECHNOLOGY
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