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书目名称Optimal Time-Domain Noise Reduction Filters影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0702937<br><br> <br><br>书目名称Optimal Time-Domain Noise Reduction Filters影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0702937<br><br> <br><br>书目名称Optimal Time-Domain Noise Reduction Filters网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0702937<br><br> <br><br>书目名称Optimal Time-Domain Noise Reduction Filters网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0702937<br><br> <br><br>书目名称Optimal Time-Domain Noise Reduction Filters被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0702937<br><br> <br><br>书目名称Optimal Time-Domain Noise Reduction Filters被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0702937<br><br> <br><br>书目名称Optimal Time-Domain Noise Reduction Filters年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0702937<br><br> <br><br>书目名称Optimal Time-Domain Noise Reduction Filters年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0702937<br><br> <br><br>书目名称Optimal Time-Domain Noise Reduction Filters读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0702937<br><br> <br><br>书目名称Optimal Time-Domain Noise Reduction Filters读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0702937<br><br> <br><br>Finasteride 发表于 2025-3-21 21:57:40
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https://doi.org/10.1007/978-3-642-19601-0LCMV filter; MDVR filter; Wiener filter; maximun SNR filter; microphone arrays; multichannel; noise reductcertitude 发表于 2025-3-22 04:52:25
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Multichannel Noise Reduction with a Rectangular Filtering Matrix,number of samples from each microphone signal. This time, a rectangular filtering matrix of size . is required for the estimation of the desired signal vector. The signal model is the same as in .; so we start by explaining the principle of multichannel linear filtering with a rectangular matrix.小教堂 发表于 2025-3-23 00:17:56
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Single-Channel Noise Reduction with a Rectangular Filtering Matrix,e than one sample at a time. As a result, we now deal with a rectangular filtering matrix instead of a filtering vector. If . is the number of samples to be estimated and . is the length of the observation signal vector, then the size of the filtering matrix is . × .. Also, this approach is more gen