signal entropy 中文意思是什麼
signal entropy
解釋
信號熵-
Semg signal complexity and entropy changes during exercise - induced local muscle fatigue
局部肌肉疲勞的表面肌電信號復雜度和熵變化 -
The thesis researches deeply the order selection for the maximum entropy spectral model. corresponding with the particularity of the short signal serials, the paper concludes the rules of the order selection for mese and presents the experiential formula
定階問題是最大熵譜分析的關鍵問題，針對簡訊號序列的特殊性，歸納出對簡訊號進行最大熵譜估計時，階數選擇的一般規律，給出定階經驗表達式。 -
There are mainly two type of algorithms used for spatial spectrum estimation : one is those based on bayesian maximum likelihood method, like the ml ( maximum likelihood ) algorithm, maximum entropy method and etc., the others are based on the spatial decomposition or projection of correlation matrix, this kind of algorithm include vector characterization method, music ( multiple signal classification ) algorithm, projection matrix method, etc. music is a classical spatial spectrum estimation algorithm that has a super high resolution and is widely used today, however, it cannot estimate doa of signals that are correlated
空間譜估計的演算法大致分兩大類:一是基於極大似然估計和最大后驗概率估計統計理論的演算法，包括:極大似然估計法（ ml ） 、最大熵法等;另一類是基於對協方差矩陣進行子空間分解或投影的演算法，包括:矢量特徵法、多重信號分類法（ music ） 、投影矩陣法等。其中， music法是一種經典的空間譜估計主流演算法，具有超強的分辨性能，但它無法實現對相干信號進行測向分辨。 -
Entropy of an image is to express the smoothness or homogeneity of the image. while computing in a local window, if there exist edges, the local image will not be homogenous, variation of the grayness will be sharp and the entropy obtained will be low. otherwise, the entropy will be high. given the threshold of entropy, it can be determined whether or not exist edges. because entropy operator is sensitive to noise, the effect is bad if it is directly used to detect edges. in view of the deficiency, the paper comes up with an edge detection method in which entropy operator is combined with noise removal. if the entropy computed is higher than the threshold, it will be necessary to determine whether it is caused by noise or by edges. thus edge detection and noise removal can be made at the same time. with this method satisfactory effect has been achieved by experimenting upon image with low ratio of signal to noise
圖像的熵用來刻劃圖像的平滑性或均勻性.在圖像的局部窗口中計算時，如果窗口中存在邊界，則窗口中的圖像不均勻，其灰度變化急劇，計算出的熵小；反之熵大.設定熵的閾值，即可判斷是否存在邊界.由於熵運算元對噪聲很敏感，直接用它進行邊界檢測，效果很差.文中針對這一缺陷，提出將熵運算元與去噪相結合的邊界檢測法，如果計算出的熵大於閾值，要判斷是噪聲的出現所引起，還是邊界的出現所引起，這樣，邊檢測邊界邊去噪聲.用該方法對信噪比較低的圖像進行實驗，得到了滿意的效果 -
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
我們還對信號進行了相空間重構，計算了信號的關聯維數、最大lyapunov指數、近似熵和復雜度這幾個非線性特徵量，我們發現，心率信號的吸引子是奇怪吸引子，關聯維數介於5到7之間，具有分維的特徵，其最大lyapunov指數大於0 ，其近似熵值和復雜度值明顯區別于噪聲，這說明心率信號不是隨機噪聲，它是服從確定性動力學規律的高維混沌信號。 -
Based on the information theory, the algorithms such as maximum entropy and minimum mutual information have been presented by researchers in the area of signal processing, which are usually applied to solve bss problems
由於關于混合信號的信息完全未知，因此將該過程稱為盲源信號分離。目前國內外主要採用基於信息論原理的最大嫡、最小互信息量來解決bss問題。 -
It also studies the influencing factors including sampling frequency, pd waveform, decline time, time intervals between pd pulses, mother wavelet, center frequency of interference, entropy threshold value and snr. in addition, it applies wavelet packet method （ wpm ） for non - stationary signal de - noising in on - line pd monitoring and analyzes the processing results under different pd waveform, sampling frequency and noise level. firstly, the curve of pd
基於小波包變換的非平穩信號消噪演算法（ wpm ）已較為成熟，本文將其應用於局部放電在線監測，通過研究其對不同局放波形、采樣率、噪聲水平下的處理效果，首次提出了理想白噪聲條件下提取局部放電信號的曲線，分析了各種因素對該演算法下信號失真的影響。 -
Super resolution pitch detection based on band - partitioning spectral entropy and signal decomposition in dct domain
分帶譜熵與信號分解的高精度基音檢測演算法 -
This paper studies the helicopter, the propeller - driven aircraft and the turbofan jet airplane echo modulating feature parameter model and analyses the echo signal feature. it gains the target echo ’ s the cyclical modulation feature by using the complex ar frequency range bispectrum slice. because traditional method in extraction airborne radar ’ s radiant signal feature time has certain insufficiency, this paper proposes the approximate entropy and the norm entropy as the passive feature parameter in the airplane
由於傳統方法等在提取機載雷達輻射源信號特徵的時候存在著一定的不足，本文提出把近似熵和范數熵作為飛機目標識別的無源特徵參數，給出了提取相應特徵熵的演算法，實現對機載雷達輻射源信號的識別，通過和機載雷達類型的匹配，實現對目標的識別。 -
Application of wavelet transform and wavelet entropy in the characteristic study of sleep electroencephalogram signal change
小波變換和小波熵在睡眠腦電信號變化特性研究中的應用價值 -
Wavelet packet decomposition based on entropy threshold for white - noise rejection in pd signal
基於門限值小波包變換抑制局部放電白噪干擾 -
Radar emitter signal recognition based on entropy features
基於熵特徵的雷達輻射源信號識別 -
This thesis analyses the vibration signals of measured point 1 of 2 # set in a generating plant, by applying the method of analyzing sin signal which uses " sym8 " wavelet packet, eight level and " shannon " entropy to de - noise
對汽輪發電機組的振動信號運用分析sin信號的方法進行了降噪處理，效果較好。本文對某發電廠正在運行的1 #和2 #汽輪發電機組進行了振動測試，採集到了可靠的振動信號。
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