threshold noise 中文意思是什麼
threshold noise
解釋
門限噪聲-
We use fuzzy mathematical morphology to remove noise and dust which can lower noise successfully and also make up a loss of intensity caused by fluorescence blench. to acquire the target region, we purpose automatic gridding method based on image segmentation for image with irregular spots, it ' s segmentation through threshold. this method is presented simply and fast
在網格定位中，本文針對信號點不規則的晶元圖像提出了基於圖像分割的自動定位方法? ?閾值分割，該方法簡單快速，但對于光密度分佈不均勻的信號點，可能會去掉部分微弱信號，降低了計算的準確性。 -
This thesis studies the law of affecting de - noise result and the selection of the threshold and the wavelet function, the combination of wavelet and fft in the fault diagnosis of turbine - generator sets : by the de - noise anslysis of blocks and sin signals, concludes : to blocks signals, usually adopts soft threshold ; the law of affecting de - noise result is when use wavelet auto - de - noise, with the increasing of decomposed level, the de - noise result becomes worse while the level blow the 3, when the level above 3 and when uses wavelet packet, it is the other way round ; the best de - noise methods of the signal is that uses " dbl " wavelet function, three level, soft and " rigrsure " threshold
本文研究了分解層數對消噪結果影響的規律和閾值、小波函數的選取，結合小波分析與fft分析診斷汽輪發電機組的故障。通過對brocks和sin兩信號的分析，得出：對blocks信號進行分析一般採用軟閾值；分解層數對消噪結果影響的規律為用小波自動降噪在分解層數小於3時，隨著分解層數的增加，消噪結果變好，反之，則變差，用小波包降噪時隨著分解層數的增加，消噪效果變好；適宜選用dbl小波軟rigrsure閾值自動消噪。 -
After scanning the object image and labeling the connected component, the background and foreground noise could be removed easily by threshold value area expunction
該方法僅需對圖像作一次全掃描即可標記物體所有連通部分，統計標識號，根據閾值面積消除法即可快速去除圖像中所有前景和背景噪聲。 -
Output can be obtain, next we use our designed the wavelet soft threshold to select result of the wavelet transform, finally, we give the selected result reversal wavelet transform. it is obvious : the wavelet soft threshold is important to improve the quality of the gray image processing. i give the donoho wavelet soft threshold a modified value method, which has a relation with ratio of signal - noise. i made full use of discrete hop field single feedback neural network, and nonlinear steady of automatic system at last, i obtained a steady limited ring, give the energy function an order differential a optimal
我的思路是：改造現有圖形結構，先建立能反映信噪比大小且含待定參數k的表達式，然後通過離散型h0pfi舊單層反饋神經網路，再結合前邊的混合濾波器構成一個非線性控制系統，寫出對應的網路函數，利用相平面法和李雅普諾大穩定性的判據，得到一個穩定的極限環，從而確定出參數卜的范圍，進而再對原來的小波軟閾值進行修正，用修正後的值作為小波閾值。 -
There must be a threshold of thermal noise.
必有一個熱噪聲的門限值。 -
Combining the basic laws of psychophysics and signal detection theory, we use two - alternative forced - choice ( 2afc ) to study the threshold change of human electric sense under different noise levels
在心理物理實驗中，結合心理物理學和信號檢測論的基本原理，採用了二間隔的強迫選擇法（ 2afc ）作為實驗方法，研究不同噪聲量級情況下人體電感覺閾值的變化。 -
Fast algorithms of both discrete and orthonormal wavelet and wavelet packet coefficient are diagrammatized to be introduced. daubechies wavelet is applied to help to discuss the application and test on signal filtering and noise reduction with the principle and threshold implementation ; the basic principle to pickup the fault characteristics is introduced mainly about the relations between the maximum module and signal saltation point and how to characterize the saltation point with lipschitz exponent
展示了離散正交小波變換的mallat快速演算法和小波包系數分解的快速演算法；重點應用daubeches小波探討了小波變換在信號濾波去噪中的應用和實驗，闡述了其基本原理和通過閾值化處理實現濾波的具體方法；探討了用小波變換進行故障特徵提取的原理，說明了小波變換模極大值和信號突變點之間的關系以及怎樣用李氏指數來表徵突變點的性質。 -
When the input noise is the single - peak gaussian noise, the noise can improve the signal correlation only for the sub - threshold signal, i. e. subthreshold stochastic resonance ( sr ) exists
當輸入噪聲為單峰高斯噪聲時，輸入信號在閾下時噪聲才能改善信號的相關性，即隨機諧振現象存在。 -
According to the different characteristics between signal and noise on wavelet transform domain, also considering the voiced and unvoiced speech has different features, a modified method of speech denoising which is using a changing threshold at different scales is proposed
摘要分析了信號和噪聲在小波域的不同特徵表現，並根據語音中濁音和清音的特點，提出了一種改進的多尺度多閾值的小波域語音去噪方法。 -
In order to reduce the musical residual noise and the background noise, a speech enhancement method based on masking properties of the human auditory system is described. this method uses bark wavelet packet transform to simulate the frequency feature of human auditory model to get the threshold
本文以最大限度減少殘留噪聲和背景噪聲為目的，採用bark子波分析的方法模擬人耳基底膜的頻率分析特性來進行語音增強，重點進行模擬人耳聽覺掩蔽效應來確定除噪閾值的研究。 -
In the paper, we describe the whole configuration of the joint transform correlator ; introduce the correlative theories of joint fourier transform in detail ; in order to achieve better correlation result, the nonlinear processing of joint transform power spectrum ( jtps ) is put forward, the effect of jtps laplace sharpening and binary processing to the correlation image is given ; the method of the best binary threshold is determined ; we analyse the correlation image, present the way that removes liquid crystal diffraction spot, direct current spot and image noise, and binarize the correlation image finally
本論文主要對提出的聯合變換相關的整體結構進行了描述；詳細介紹了聯合傅里葉變換的相關理論；為了得到更好的相關結果，本文提出對聯合功率譜進行非線性處理的方法，給出了聯合變換功率譜的拉普拉斯銳化和譜的二值化處理對相關峰圖像的影響及二值化最佳閾值的確定方法；對相關峰圖像信息進行了分析；提出了消除液晶衍射光斑、直流光斑和圖像噪聲的方法；最後對相關峰圖像進行了二值化處理。 -
Thirdly, in the environment of labview, several kinds of vis used for sensor signal test are designed, including wave generation, time domain measurement, filter disposal, frequency analysis, etc. after that, wavelet analysis in the application of one - dimensional signal de - noise is studied, threshold and translation invariance wavelet de - noise are realized, and wavelet de - noise vi for zero drift signal of the fiber optic gyro in fcs is designed using labview
接著，在labview環境下開發了多種用於傳感器信號測試的虛擬儀器，具有波形發生、時域測量、濾波處理、頻譜分析等多種功能。隨后，研究了小波分析在一維信號消噪中的應用，實現了labview環境下的閾值法和平移不變量法小波消噪，並利用labview設計了飛控系統中光纖陀螺零漂信號的小波消噪儀。 -
In this paper, the contrast of original image is enhanced by nonlinear transformation based on the characteristics of grain image ; after comparing several methods of threshold segmentation and analyzing their performance and applicability on grain image, the adaptive threshold segmentation based on gradient image is presented ; the noise of binary image is reduced with morphological filter, the hollow in binary image is filled in and a recognition algorithm is designed to remove agglomerate particle ; on the basis of mathematical morphology two methods are adopted to segment agglomerate grains that are not agglomerated tightly ; the parameters of size and shape, perimeter, area, diameter, complexlity, longest feret diameter, shortest feret diameter etc, are extracted. this technique is applied in measurement of pearl powder ' s particle size
本文根據粒度圖像的特點，採用非線性對比度增強處理改善顆粒顯微圖像的對比度；對多種閾值分割方法進行比較，分析了它們的性能和用於粒度圖像的適用性，在此基礎上提出了一種基於梯度圖像的動態閾值分割方法；對獲取的顆粒二值圖像進行形態濾波和空洞填充，設計了識別演算法去除凝聚體；對重疊不太嚴重的粘結顆粒採用了兩種基於數學形態學的分割演算法；提取了周長、面積、粒徑、復雜度、最長feret徑、最短feret徑等大小和形狀特徵參數，對珍珠粉等粉體粒度進行了測量。 -
An automated de - noising algorithm based on the energy of wavelet packet not donoho ' s threshold algorithm is established. a gear feature vibration signal extraction method using the wavelet packet energy is proposed, which can separate gear meshing vibration, noise vibration and gear fault vibration signal from the original gearbox case vibration signal. basis pursuit ( bp ) algorithm is introduced into the filed of mechanical signal de - noising and feature extraction for the first time
第三章擺脫了donoho的閾值消噪思想，從能量的角度建立了基於小波包的自動消噪演算法；提出基於小波包能量分佈的齒輪故障特徵信號提取方法，可以將齒輪嚙合振動信號、干擾振動信號以及故障沖擊振動信號從原始齒輪振動信號中分離出來；首次將基追蹤消噪演算法引入到機械故障信號的消噪與特徵提取上，通過對齒輪故障信號的消噪，表明了它的有效性，並對影響該方法實際應用效果的因素進行了全面的分析，同時也指出了該方法存在的局限性。 -
This thesis explains the necessity of the character recognition technology of the computer at first, describe the meaning in which the handwritten numeral discerns ; pretreatment technology of handwritten numeral recognition, including two value, line segmentation, word segmentation smooth, removing noising, standardization and thinning are discussed two value concretely discusses whole threshold value, some threshold value, dynamic threshold value and utilize space information to carry on threshold, which are several kinds of common method of choosing threshold value, especially utilize space information to carry on threshold value is describe in detail ; adopting to the foundation of thinning based on mathematics morphology, thinning algorithm of serials same and thinning algorithm of protecting shape are discussed ; afterwards, according to principle ' s diagram of the on - line character recognition, by analyzing the structure feature of the handwritten numeral, this thesis has proposed the online recognition te chnology of the free handwritten numeral based on the stroke feature and the online recognition technology of the free handwritten numeral based on the multistage classifying device. detail narrated noise removing, stroke characteristic definition and discernment, distance criterion of whole word match ; then under the foundation of handwritten numeral segmentation, off - line handwritten numeral recognition is researched. especially minimum distance classifying device, tree classifying device and adaptive resonance ( art ) network classifying device is discussed at the same time, believes degree analyses are introduced to integrate a lot of classifying devices ; at the end, the typical application of the handwritten numeral recognition was briefly narrated, its application in extensive data statistics, financial affairs, tax, finance and mail sorting have been explored
二值化時對整體閾值二值化、局部閾值二值化、動態閾值二值化和利用空間信息進行閾值選取幾種常用的閾值選取方法進行討論，特別對利用空間信息進行閾值選取進行了詳細論述；在對通過對基於數學形態學的細化的基礎上，討論序貫同倫形態細化演算法和保形的快速形態細化演算法；然後依據聯機字元識別原理框圖，分析了手寫數字的結構特點，提出了基於筆劃特徵的任意手寫數字在線識別技術和基於多級分類器任意手寫數字在線識別技術，對其中涉及的筆劃識別前的噪聲處理、筆劃間特徵量的定義及識別、整字匹配的距離準則進行了詳細敘述；繼而在對手寫數字的分割的基礎下對脫機手寫數字識別進行了研究，對基於最小距離分類器字元識別、基於樹分類器的字元識別、基於自適應共振（ art ）網路的字元識別分別進行了詳細討論，並引入置信度分析將多個分類器進行了混合集成；最後簡單闡述了手寫數字識別的典型應用，對其在大規模數據統計、財務、稅務、金融及郵件分揀中的應用進行了探索。 -
2 ) set threshold in stationary wavelet domain to separate edge and noise, estimated wavelet coefficients in texture area to reconstruct the interferogram
3 ）在靜態小波域設置濾波閾值以區分邊緣和噪聲，根據map準則來確定信號的小波系數，然後重建干涉相位圖。 -
In order to study the effect of weak noise on the sound signal extraction of mouse ( mus musculus km ) inferior collicular ( ic ) neurons from environment, we examined the change in frequency tuning of neuron induced by a weak noise relative to 5 db below minimum threshold ( remt - 5 db ) of tone. 12 healthy adult mice ( 20 - 25 g, b. wt. )
本實驗旨在探討弱噪聲對小鼠（ musmusculuskm ）中腦下丘（ inferiorcolliculusic ）神經元聲信號提取的影響及其神經機制，我們選用相當于純音閾下5db的白噪聲（ whitenoise ） ，比較加入噪聲前後神經元頻率調諧曲線的變化和注射-氨基丁酸（ - aminobutyricacid ， gaba ）能受體拮抗劑荷包牡丹堿（ bicuculline ， bic ）后對該變化的影響。 -
We use a colorful noise to describe traffic flow and regard it as the uncontrolled input ( equaled to noise ). then we use the multi - rate sampling pi controller to eliminate the error caused by noise, and make the length of queue stabilize at the threshold. the availability of the strategies and stability of systems are proved by doing some analysis and simulation
文中我們將一有色噪聲看作不可控輸入的擾動，採用基於pi的多采樣速率控制器以消除由此不可控輸入所造成的對系統輸出（交換節點緩沖區隊列長度）誤差的影響，使得系統輸出（隊列長度）穩定在閾值附近。 -
This paper illustrates detailedly the thin groupware auto - adaptive recognition system ; it also illlustrates the procession of capture image and take indispensable foreclose to wipe off noise in order to get boundary easilyer. the recognition system uses " hough " transform method to make the recognition area orientation, and according to the unstable environment such as lights which leads to the change of the image ' s brightness, thresholds picture using an iterative selection method and then growing process for cell image segmentation based on local color similarity and global shape criteria, adaptively gets the best threshold to divide the washer off the background. the recognition system uses the classifier based on minimal - error - ratio bayes method to make decision after getting image characteristic
本文詳細介紹了薄形組合件自適應識別系統；闡明了圖像的分通道自動採集過程，以及對採集到的原始圖像所進行的預處理方法。通過採用哈夫變換去除偽邊緣點的方法，有效地解決了識別區域的定位問題。針對裝配零件（主要是墊片）薄、小導致圖像信息少、識別難度大，以及材質不一導致採集到的組合件圖像亮度波動等問題，提出了使用最佳閾值迭代法和使用種子填充的圖像串列分割技術，自適應地找出最佳閡值，使墊片和背景分離，從而提取墊片數目信息。 -
At last the floating threshold algorithm based on wavelet packet transform is proposed to remove the noise from the signal of dc motor measurement in the dissertation, which is proved effectively by the experimental results
提出了基於小波包變換的浮動閾值去噪演算法，並應用到直流電動機測試過程中的高頻噪聲去除過程中。
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