The wavelet analysis method, used in ICT to detect edges within a cross section is introduced.
介绍了在工业计算机断层扫描成像(ICT)中探测工件断面内边缘的小分析波方法。
In data processing, the wavelet analysis was used for the differential spectral data, so the noise was reduced and the precision of analysis was improved.
在数据处理过程中，对微分光谱数据进行了小波去噪处理，使信噪比得到了增加，从而使分析精度得到了改善。
This paper takes the wavelet analysis transform as the means to process the fault detection and diagnosis of the jointing. The research result is inspiring.
这里用分形变换的方法对焊接过程中进行初步缺陷检测和诊断，结果表明分形分析在焊接过程中缺陷检测和诊断有很好的应用前景。
This paper takes the wavelet analysis transformation as the means to process the fault detection and diagnosis of the jointing. The research result is inspiring.
用分形变换的方法对焊接过程中进行初步缺陷检测和诊断，结果表明分形分析在焊接过程中缺陷检测和诊断有很好的应用前景。
On the basis of analyzing time sequence concept, logic and application, puts forward the space sequence concept, applies the wavelet analysis on space sequence concept.
分析了时间序列的概念，在逻辑和应用的基础上，提出了空间序列概念，并将小波分析应用于空间序列概念。
That provides not only the theoretic bases for discussing the image space of wavelet transform, but also a new method to investigate the wavelet analysis theory further.
这不仅为小波变换像空间的讨论提供了理论基础，也为小波分析理论的进一步研究提供了新的途径。
The key advantage of the wavelet analysis is that, in contrast to the conventional Fourier analysis, it can be localized in the time and frequency domain simultaneously.
同传统的傅立叶分析相比，小波分析的最大优势在于可以同时在时频两方面实现局部化分析。
The example results indicated that the synthesis method based on the wavelet analysis on shortterm gas load prediction has effectively improved the prediction precision.
实例验证表明，燃气短期负荷预测小波分析综合模型有效地提高了负荷预测精度。
The wavelet analysis can divide signals into different frequency sects, and provide with showing the local character ability of signals in both time and frequency domains.
小波分析能够将信号划分到不同频段内，而且在时一频两域都具有表征信号局部特征能力。
The wavelet analysis is a key method to solve this kind of the problem because of its unique time-frequency localization characteristic, compared with traditional methods.
鉴于传统信号处理方法的局限性，小波分析以其具备时频局部特性，成为解决此类问题的一个重要方法。
That provides not only the theoretic bases for discussing the image Spaces of other wavelets transforms, but also a new method to investigate the wavelet analysis theory further.
这不仅为其它小波变换像空间的讨论提供了理论基础，也为小波分析理论的进一步研究提供了新的途径。
The wavelet analysis is applying widely to pure mathematics, applied mathematics, signal processing, speech recognition and synthesis, automation processing and image analysis etc.
小波分析已经广泛应用于理论数学、应用数学、信号处理、语音识别与合成、自动控制和图像处理与分析等领域。
The wavelet moment is a combination of the wavelet analysis and the invariant moment, it has the advantages of the both of them, so it is valuable for the engineering applications.
小波矩是小波分析和不变矩的结合，它拥有小波分析和不变矩各自的优点，具有较大的工程应用价值。
Through the filter experiment on the actual sampling signal, and compares with the common average filter algorithm, it proved the wavelet analysis algorithm has better filter effect.
通过对红外水分仪实际采样信号的滤波试验，并与一般平均滤波算法相比较，证明其具有更好的滤波效果。
An abnormality diagnosis model was developed for hydraulic concrete structures operating with cracks occurring in their bodies by use of the wavelet analysis and cusp catastrophe theory.
对于带缝运行的水工混凝土结构，用小波分析和突变理论相结合的方法，建立裂缝转异诊断模型。
The basic concept of the wavelet analysis, binary wavelet decomposition and reconstruction algorithm are introduced, and the peculiarities of the frequency of logging signal are discussed.
介绍了小波分析的基本概念和二进小波的分解及重构算法，探讨了测井信号的频谱特征。
The results showed that it is practicable to use the wavelet analysis method in vibration fault diagnosis, and it also has reference value on other complicated machines' vibration diagnosis.
结果表明，小波分析方法用于柴油机的振动故障诊断是有效可行的，对其他复杂机械的振动诊断同样具有参考价值。
The multiresolution image representation based on the wavelet analysis is introduced. By this way, the image resolution can be decreased in keeping with the human visual system characteristic.
本文基于小波分析提出由高分辨率图像可得到各种较低分辨率图像的多分辨方法符合人的视觉系统特性。
Compared with the wavelet analysis, the dynamic reference waves are more flexible and effective in extracting the available fault traveling waves in the complex environment with serious noise.
和小波分析法相比，动态的参考波对于在复杂的干扰环境下提取有用的故障波形更加灵活、有效。
By means of the wavelet analysis, non-steady signals are analyzed, the fault feature vectors of fault are successfully extracted and this effective method is employed to identify the fault pattern.
研究了小波分析在非平稳信号分析的实际应用，成功地通过小波分析提取故障信号的特征信息，为识别故障类型提供了有效的分析手段。
In view of the uncertainty of the load and the randomness of the response signal, the wavelet analysis is used to process the collection of vibration signals, so as to avoid the observation overflow.
针对结构承受荷载的不确定性以及响应信号的随机性，运用小波分析对振动信号进行采集处理，避免了观测溢出。
But in wavelet parameters optimization problem, wavelet analysis in the application of the theory to the actual fault diagnosis system, has a large number of practical work to do.
但在小波参数的最优化问题上，在将小波分析的理论应用到实际的故障诊断系统中，还有大量的实际工作要做。
Furthermore, in order to make a necessary foundation for further research, the relevant knowledge about wavelet analysis and generalized functions is introduced briefly.
并简要介绍小波分析及广义函数的一些基本原理与相关知识，以此作为本课题研究的必备基础。
The third part USES wavelet analysis and Mathematical Morphology to detect the image edge, and contrasts the two results, we have gotten respective apply condition and good or evil.
第三部分分别使用小波分析和数学形态学进行了数字图象边缘检测，并将两者的检测结果进行了对比，得出了各自的适应条件和优劣之处。
Having good time-frequency localization character, and correctly identifying singularity point in fault signal, Wavelet is the main analysis method in this paper.
小波变换具有良好的时频局部性，具有变焦距的特点，对故障信号中的奇异点能够准确识别，是论文中应用的主要分析方法。
The method uses wavelet transform and principle component analysis to preprocess fault signal, afterward training and testing wavelet neural network with the preprocessed fault characteristic data.
该方法首先利用小波变换和主成分分析对故障信号进行预处理，然后用处理后的故障特征数据对小波神经网络进行训练和测试。
The use of empirical mode decomposition (EMD) method and wavelet analysis in combination is explored for the detection of changes in the structural response data from structural damage diagnosis.
采用经验模式分解(EMD)与小波分析相结合的方法探讨结构响应数据信号，进行建筑结构损伤检测诊断。
Compared with deconvolution method, the well log curves transformed by wavelet analysis contain more detailed information and reach higher vertical resolution.
该方法与反褶积方法比较，小波变换后的测井曲线更能反应细节信息，具有更高的纵向分辨率。
The features of gene expression are extracted by the wavelet multi-resolution analysis, the features are classified by the support vector machines and BP neural network methods.
采用小波多分辩率分析方法提取基因表达的特征，利用支持向量机和BP神经网络方法进行分类。
The features of gene expression are extracted by the wavelet multi-resolution analysis, the features are classified by the support vector machines and BP neural network methods.
采用小波多分辩率分析方法提取基因表达的特征，利用支持向量机和BP神经网络方法进行分类。
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