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source signal in Chinese

Pronunciation:
How to pronounce "source signal""source signal" in a sentence

Translationmobile phoneMobile

  • 震源信號

Examples

  • Blind separation technique of modulatory fault source signal
    調(diào)制故障源信號盲分離技術(shù)
  • Aiming at the time - difference of the same source signals , the wavelet characteristic of singularity detection is applied
    對同源信號的時差問題，論文中運用小波檢測奇異點的特性來計算。
  • Combining the blind beamforming with the estimation of doa , the doa can be estimated at the same time when the source signals are recovered
    并將盲波束形成與目標(biāo)方位估計相結(jié)合，實現(xiàn)在捕獲、恢復(fù)目標(biāo)源信號的同時，估計出目標(biāo)的波達(dá)方向。
  • Bss problems are to separate or extract individual source signal from a set of mixture signals . except that the source signals are assumed to be independent , no apriori information is known about the mixture signals
    Bss問題是從某類混合信號序列中分離或估計各個未知源信號的過程，其中假設(shè)源信號是相互統(tǒng)計獨立的。
  • We separate the linear mixed signals using the fourth order cumulants and independent component analysis technology . the source signals , which are separated , are applied to speaker recognition and they can be well recognized
    本文運用四階累積量法和獨立分量分析技術(shù)成功地將線性混疊語音信號分離，再將分離出的源信號用于說話人識別，可較好地識別出說話人。
  • Blind source separation ( bss ) problem is to separate or extract individual source signal from a set of mixed signals , assuming the source signals are independent and no a - prior information is known about the mixed signals
    盲源分離問題是從某類混合信號序列中分離或提取出各個未知源信號的過程，其中假設(shè)源信號是相互統(tǒng)計獨立的，人們對混合信號的信息完全未知。
  • Blind beamforming ( bbf ) is concerned with the reconstruction of source signals from the outputs of a sensor array without a priori information of the direction of the desired source , relying instead on signal characteristics and array structures
    盲波束形成無需知道目標(biāo)波達(dá)方向等先驗信息，直接利用信號、基陣自身的特性，就可從基陣的輸出采樣信號中恢復(fù)出期望信號。
  • Based on theoretical studies on these algorithms , by means of computer simulation and the water tank experiment , we analyzed the performance of these algorithms in uniform linear array , which included the separation and reconstruction of source signals and doa estimation performance
    在詳細(xì)分析各種算法內(nèi)在機(jī)理的基礎(chǔ)上，針對均勻線列陣，通過大量的計算機(jī)仿真實驗與水池實驗數(shù)據(jù)處理結(jié)果，分析、討論了幾種算法對目標(biāo)源信號的分離、捕獲能力以及方位估計性能。
  • During the past decade , blind source separation - bss has been a focus in the research area of signal processing . ranging from wireless communication to medical signals processing , to image enhancement and to audio mixtures separation , bss is a powerful tool to tackle those problems because it can reconstruct the original signals from the observed signals without any prior knowledge of the mixing system and source signals
    盲信號分離技術(shù)是近年來信號處理領(lǐng)域的一個研究熱點，由于其能夠從觀測的混合信號中恢復(fù)出原始信號，而對原始信號和混合系統(tǒng)的先驗知識要求很少，因此在無線通信、醫(yī)學(xué)信號處理、圖像增強(qiáng)和語音分離方面有著廣泛的應(yīng)用。
  • Two primary mathematical tools used in this dissertation are principal component analysis ( pca ) and blind signal analysis ( bsa ) , which are both data - driven methods . pca is not only used as feature extracting method ( where process variables are subjected to multivariate normal distribution ) , but also as a tool for dimension reduction ; bsa is used to extract independent features or process blind source signals from process information in information theory sense , which is more effective than pca in describing the process
    主元分析方法不僅作為一種過程特征的提取方法(在過程信息服從多元正態(tài)分布的情況下) ，而且也作為一種過程數(shù)據(jù)降維的主要工具(在過程盲源信號提取的情況下) ；盲源信號分析是從信息論的角度，從過程信息中提取出盡可能獨立的過程特征信號或過程原始信源信號，它具有比主元分析更好的刻畫過程運行特征的性能。
  • More examples：  1  2  3
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