This paper presents a method of radar target identification using wavelet transforms and rough sets.
本文提出了一种新的基于目标一维散射中心匹配的雷达目标识别方法。
Basic theory is thoroughly described and illustrated, with a detailed explanation of how discrete wavelet transforms work.
基础理论被完全描述并且说明，有一个子波变换工作多分离的详细的解释。
There are two main transform domain methods, one is to use the discrete cosine transformation (DCT); the other would be the use of discrete wavelet transforms (DWT).
目前主要有两种变换域方法，一种是使用离散余弦变换(DCT)，另一种是使用离散小波变换(DWT)。
A novel method is proposed in this paper by research on complex wavelet, in which phase information of complex wavelet transforms is used to detect frequency and harmonics.
本文通过对复小波的研究发现复小波变换的相位信息能用于频率检测和谐波分析，提出了基于复小波变换相位信息的频率和谐波检测新算法。
EMD similars the wavelet transforms, the decomposition result is from high frequency to the low frequency distribution, namely the noise mainly concentrates in first several.
经验模式分解的主要思想类似小波变换，分解结果是由高频到低频分布的，即噪声主要集中在前几层。
The paper analyzes the method of low frequency signal injection, which is usually used to detect DC system grounding fault, and advances the method based on wavelet transforms.
分析了低频信号注入法，并且针对其缺陷提出了基于小波变换的检测方案。
By studying three dimensional discrete wavelet transform (3d DWT) core algorithm in deepness, the paper divides it into three one dimensional discrete wavelet transforms (1d DWT).
通过深入研究三维离散小波变换(3dDWT)核心算法，将其分解为3个一维的小波变换(1d DWT)。
Because complex wavelet transforms can exactly identify amplitude and phase information in signal to be dealt with, they are suitable for detection of fault signals in power system.
复值小波变换能准确分辨出信号中所包含的幅值信息和相位信息，因而，适用于电力系统的故障信号的检测。
Base on the basic model of orthogonal wavelet transforms, principle of remote sensing image fusion is discussed by using orthogonal wavelet decomposition and reconstruction in this paper.
在给出小波变换基本模型的基础上，探讨了采用小波正交分解与重构来进行遥感信息融合的基本原理。
Although wavelet transforms (WTs) are being used to process fault signals of power system widely. Wavelet transforms can only filter white noises and are useless to filter colored noises.
小波变换在电力系统的故障信号处理中得到广泛地应用，然而，小波变换只能消除白色噪声，对有色噪声不起作用。
Materials and methods Comparing the different characteristics between the Fourier exchange and wavelet transforms. Results the wavelet transforms is more suitable for medical tinge treatment.
材料与方法比较傅里叶变换和小波变换的特点、结果小波变换适用于医学影像处理。
Wavelet transforms are used to compress image and smooth edge of liver region from abdomen MRI. The results of image segmentation are evaluated based on the liver region determined by doctor.
应用小波变换对腹部MRI进行图像压缩与平滑化处理，应用边缘检测技术进行边缘数据与肝脏特征值的提取，并结合医师确定的肝脏区域进行图像分割效果的评价。
Our analysis shows that directional wavelet transforms can better reflect the edge information of images because they better corresponds to the characteristics of image direction and texture.
比较了方向小波变换和传统小波变换在图像边缘检测中的不同之处。分析得出方向小波变换更符合图像的方向、纹理特征，因而更能反映图像的边缘信息。
Due to wavelet transforms efficiently overcoming the limitations of Fourier transform in dealing with unstable and complicated signal, they are popular in image compression and signal processing.
由于小波变换有效地克服了傅氏变换在处理非平稳的复杂信号时所存在的局限性，因而在图像与信号处理领域受到了广泛的重视。
Because of the prominent advantages of quantum computation compared to classic computation, implementation of quantum wavelet transforms has profound significance to its completion and application.
由于量子计算相比于经典计算的突出优越性，量子小波变换的实现对于小波变换的理论完善和实际应用具有重要的意义。
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。
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。
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