1、

Firstly, it was proved that the multistage wiener filter ( MWF) implemented by the correlation subtraction algorithm ( CSA) was a unitary MWF and that the matched filters were equal to the corresponding basis vectors of the rank reducing subspace in the CSA-MWF.

证明了由相关相减算法实现的多级维纳滤波器是一种酉多级维纳滤波器,并且其各级的匹配滤波器与对应的降秩子空间的基向量相等。

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2、

Based on the results about CSA proven, the iterative CSA for implementing the MWF was proposed by applying the backward iteration to the CSA-MWF.

在证明结论的基础上,将后向迭代算法应用于相关相减算法多级维纳滤波器,提出了多级维纳滤波器的迭代相关相减实现算法。

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3、

Nine basic window functions are defined, MWF's basic properties and oprational rules are analyzed. Finally, an example is given, which shows that the study of MWF and it's circuits has important scientific significance.

文中定义了九种基本窗口函数,分析了MWF的基本性质和运算规律,最后辅以实例,指出对于MWF及其电路的研究有很好的发展前景。

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4、

Daimosol S-300 a clean bio stable MWF for medium severe grinding and easy machining operations of ferrous materials.

是一种生物稳定性高之切削油,适用于铁金属的中度研磨及加工。

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5、

Two typical multistage iterative reduced-rank ( MIRR) methods, multistage nested wiener filtering ( MWF) algorithm and auxiliary vector filtering ( AVF) algorithm were deeply analyzed and unified to the same reduced-rank frame on a certain enhanced condition.

本文深入研究了多级维纳滤波(MWF)和辅助向量滤波(AVF)两种典型多步迭代降维方法,在一定加强条件下将这两种方法统一到同一降维框架内。

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