ica independent component analysis 中文意思是什麼

ica independent component analysis 解釋
獨立分量分析
  • ica : ICA ＝ International Cooperative Alliance （聯合國）國際合作社聯盟。
  • independent : adj 1 獨立的，自主的，自治的，有主見的。2 自食其力的，收入足夠維持閉居生活的。3 願意獨立的，獨立...
  • component : adj 構成的，組成的，合成的，成分的。 component motion 【物理學】分運動。 component part 組成部分...
  • analysis : n. （pl. -ses ）1. 分解，分析；【數學】解析。2. 梗概，要略。3. 〈美國〉用精神分析法治療（＝ psychoanalysis）。
  1. Independent component analysis, ica

    對獨立成分分析
  2. Aimed at the acoustic signals from heavy sizing - press and rolling bearing rig, a preprocessing of autocorrelation for independent component analysis ( ica ) is proposed

    摘要以大型軋鋼機和滾動軸承試驗臺為研究對象，應用獨立分量方法來分離機器的聲音信號，並提取其狀態特徵。
  3. To utilize these advantages, we apply independent component analysis ( ica ) on dsc - mri images, then we can get output images, which are independent each other

    結合這時間與空間兩項的優點，將獨立成分分析法應用在動態血流灌注影像上，我們便可以得到互為獨立的各組織范圍的影像。
  4. The independent component analysis ( ica ) is a branch of the blind source separation, which has become an important part in signal processing and data analysis

    盲信號分離在信號處理領域中日益顯示出其重要性，而獨立分量分析是其中的重要組成部分。
  5. Independent component analysis ( ica ) is a new multi - dimensional signal processing technology developed from blind source separation of late years. some scholars have brought forward a new polarimetric speckle reduction method by using independent component analysis which based on the multi - polarimetric trait of polarimetric sar and the independence between speckle and texture of sar imagery. while the algorithm thinks that there is only one real scene in polarimetric sar source images, so they get only one recovering image in the procedure of image separation and lose polarimetric property

    獨立分量分析是近年來由盲源分離技術發展來的一種新的多維數字信號處理技術，通過計算數據的高階統計信息，可以僅從觀測信號中估計出互不相關且盡可能相互統計獨立的被未知因素混合的原始信號的估計信號，從而幫助實現信號的增強和分析。
  6. The main point of this project is to research the theories and applications of artificial neural network ( ann ) which is suitable for large scale science data mining. especially, our research focus include : dimension reduction techniques based on independent component analysis ( ica ) and wavelet - based denoising or compressing techniques for feature extraction in scientific datasets which have complex features ; classify and clustering techniques of ann combination with data grid, back - propagation neural network, self - growing multilevel self - organizing map for large scale knowledge founding in sdm

    特別深入研究以獨立分量分析（ ica ）為主的降維技術、以小波神經網路為主的壓縮降噪技術解決科學數據特徵復雜不便識別的問題;以同網格結合的神經網路、誤差反向傳播的bp神經網路、自適應多級自組織特徵映像網路為主的分類、聚類技術解決科學數據挖掘中的大規模知識發現問題。
  7. Based on the existing spectral independent component analysis ( spectral ica ) and non - negative constrained decomposition, a moving time window is introduced, and multiple dominant spectral components are extracted within the short - time window

    結合已有的頻域獨立成分分析方法以及帶約束的非負分解處理，引入時間滑動窗口，在短時窗內動態提取多重主導功率頻譜。
  8. In this paper, the principle of spread sequence communication and all kind of the current multi - user detection techniques and the independent component analysis ( ica ) algorithm are respectively analyzed completely in chapter ii, chapter iii and chapter iv. based on the statistical feature of multi - user signal that the signal of every user ' s and every channel is statistical independent with each other and take the same distribution, the mathematical model of the received multi - user signal is fully researched, then the blind signal detection algorithm is introduced into the multi - user signal detection, two new algorithms of multi - user detection are proposed : multi - user detection based on the delay estimation of downlink using ica in ds - cdma and based on ica post processing matched filter multi - user detection

    本文比較全面的從第二章到第四章分別介紹了cdma擴頻通信的原理和現有的各種多用戶檢測技術以及獨立分量分析（ ica : independentcomponentanalysis ）這種盲源分離演算法，並在此基礎上，從多用戶信號的統計獨立同分佈的統計特徵出發，分析研究了cdma通信中多用戶信號的數學模型，將盲源分離技術應用到多用戶信號檢測當中來，提出了兩種盲多用戶檢測的策略：基於獨立分量分析的下行鏈路延遲估計的多用戶檢測演算法；基於獨立分量分析后處理的匹配濾波多用戶檢測。
  9. Based on ica post processing matched filter multi - user detection lets the output of traditional matched filter to initialize the ica iterations, not only the known spread information of interesting user is used to overcome the uncertainness of ica, but also the character of statistical independence is used. the simulation results show that it advances the ability of traditional detector when the signal - noise - ratio is large. keywords code division multiple access ; independent component analysis ; channel estimation ; matched filter ; blind multi - user detection

    基於ica后處理的匹配濾波多用戶檢測是用傳統的檢測器的輸出來初始化ica的迭代，它不但充分利用多用戶信號的已知信息，克服了ica的不確定性問題，同時也充分利用了多用戶信號的統計獨立性，模擬實驗結果證明這種多用戶檢測演算法在高信噪的情況下，誤碼性能改善隨著信噪比的提高不斷增加。
  10. Independent component analysis ( ica ) technology developing is a later theory or method in fields of signal processing, but it was important that rapidly become a part of constitution of signal processing fields, and its developing tends gradually to maturity and systematization

    獨立分量分析技術（ ica ）是信號處理領域發展較晚的一種理論與方法，已迅速成為該領域內重要的組成部分，且其發展逐漸趨向成熟化與系統化。
  11. Based on the research of ear recognition with independent component analysis ( ica ), a new compound structure classifier ( cscer ) ear recognition model was proposed

    摘要在基於獨立分量分析的人耳識別方法研究基礎上，提出復合結構分類器的人耳識別通用模型。
  12. Independent component analysis ( ica ) is a multi - dimensional statistical analysis method developed in the 90 ' s of the 20th century and used to analysis the mutually independent nongaussian signals

    獨立分量分析（ ica ）是90年代中期發展起來的一種多維統計分析方法，它的研究對象是相互獨立的非高斯信號。
  13. Two common defects are founded in bss algorithms based on independent component analysis ( ica ) : the selection of none - linear function ( nlf ) in ica depends on the kurtosis of original signals, which degrades the performance of separation seriously when the observed signals are the mixture of super - gaussian and sub - gaussian signals

    2 .對一些現在流行的基於獨立分量分析的盲分離演算法進行深入研究后，發現其存在以下兩點共同缺陷:由於演算法中非線性函數的選取依賴于源信號的峭度性質，當觀測信號為超高斯和亞高斯混合信號時，分離演算法性能急劇下降。
  14. The problem is treated as one of blind source separation ( bss ), which can be performed by techniques such as independent component analysis ( ica ). in this thesis, a data - adaptive technique very similar to ica called snmf ( non - negative

    傳統的解決這個問題的方法是用多個麥克風，在不同的位置上得到這段混合的聲音信號，以便獲取足夠的、相對獨立的信息來分離出源聲音信號。
分享友人
分享到 Line

分享到臉書