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approximate entropy in Chinese

Pronunciation:
How to pronounce "approximate entropy""approximate entropy" in a sentence

Translationmobile phoneMobile

  • 近似熵

Examples

  • Information entropy and approximate entropy of sleep eeg
    睡眠腦電的信息熵和近似熵
  • Noisy speech endpoint detection based on approximate entropy
    所以提出了一種基于線譜對系數(shù)
  • Effects of noise to the approximate entropy of the chaotic system
    噪聲對混沌系統(tǒng)近似熵的影響
  • Fast algorithm of dynamic approximate entropy and its application in heart rate variance analysis
    動態(tài)近似熵快速算法在心率變異研究中的應(yīng)用
  • Based on the introduction of approximate entropy and human activity effect e , runoff series complexity of the yellow river was analyzed
    摘要在引入近似熵并給出人類活動影響程度e的基礎(chǔ)上，對黃河徑流序列的復(fù)雜性進(jìn)行了分析。
  • In this article , the prime task is the reasarch of extraction airplane ’ s periodic signature of modulation , the approximate entropy , the norm entropy , obtaining the sensor confidence level as well as structuring realization target identification intellectualized type fusion model and the algorithm
    本文主要工作是研究提取飛機(jī)目標(biāo)的調(diào)制周期特征,近似熵、范數(shù)熵,獲取傳感器可信度以及構(gòu)造實(shí)現(xiàn)目標(biāo)識別的智能化類型融合模型和算法。
  • This algorithm uses approximate entropy index ' s projection pursuit based on real coding genetic optimize algorithm ( rcgoa - pp ) to project the targets information hided in the high - dimensional data into low - dimensional space and then extract small targets with histogram image segmentation method
    該算法用基于近似相對熵的實(shí)碼遺傳優(yōu)化投影尋蹤方法( rcgoa - pp ) ，有效地將高維數(shù)據(jù)中隱藏的目標(biāo)信息集中投影到低維空間中，并用直方圖分割的方法提取出小目標(biāo)。
  • Based on a large amount of experimental data , nonlinear analysis , such as complexity theory , and approximate entropy ( apen ) which is adopted systematically in the fluidization research the first time , are implemented in the time series analysis of pressure fluctuation and particle concentration in gas - solid fluidized beds , and the nonlinear characteristics of fluidized beds are discussed comprehensively
    本文在大量實(shí)驗(yàn)數(shù)據(jù)基礎(chǔ)上，將非線性方法，包括復(fù)雜性理論，以及首次被系統(tǒng)引入流態(tài)化研究的近似熵，應(yīng)用到氣固流化床壓力及顆粒濃度脈動時間序列分析中，較為系統(tǒng)地探討了流化床的非線性特征。
  • We reconstructed the phase space and calculated the nonlinear parameters such as correlation dimension , the largest lyapunov exponent , approximate entropy , and l - z complexity of the data . it can be conclud from the results that the reconstruction of heart beat rate signal is strange , its correlation dimension is between 5 to 7 and have the character of fractal dimension , its largest lyapunov exponent is larger than zero , its approximate entropy and l - z complexity are obviously differ from noise . we can draw a conclusion from all above : the heart beat rate signal is n ' t simple noise , it is high dimensional chaos obeys certain dynamical law
    我們還對信號進(jìn)行了相空間重構(gòu)，計算了信號的關(guān)聯(lián)維數(shù)、最大lyapunov指數(shù)、近似熵和復(fù)雜度這幾個非線性特征量，我們發(fā)現(xiàn)，心率信號的吸引子是奇怪吸引子，關(guān)聯(lián)維數(shù)介于5到7之間，具有分維的特征，其最大lyapunov指數(shù)大于0 ，其近似熵值和復(fù)雜度值明顯區(qū)別于噪聲，這說明心率信號不是隨機(jī)噪聲，它是服從確定性動力學(xué)規(guī)律的高維混沌信號。
  • At first , construct ten sets of surrogate data for each emg data , then calculate the correlation dimension ( dcorr ) , correlation time , maximum lyapunov exponent ( a , ) , l - z complexity and approximate entropy ( apen ) of both the original emg data and surrogate data , and then compare them
    構(gòu)造這四例肌電信號的代替數(shù)據(jù)(各十組) ，分別計算原數(shù)據(jù)及其代替數(shù)據(jù)的關(guān)聯(lián)維、關(guān)聯(lián)時間、最大李雅普諾夫指數(shù)、 l - z復(fù)雜度和近似熵，我們發(fā)現(xiàn)，四例原數(shù)據(jù)的以上所有特征量都與各自所對應(yīng)的十組代替數(shù)據(jù)存在明顯差別。
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