小波变换作为一种新型的信号处理方法，因其可以对信号进行多分辨率分析并有高效算法，所以在DSP上得到了广泛应用。
As a new signal processing method, wavelet transform has been widely used on DSP, for it can analyze signal with multi-resolution and has efficient algorithm.
文章提出一种基于多分辨率学习的正交基小波神经网络结构的设计方法，网络权值的学习采用阻尼递推最小二乘算法。
A designing method of wavelet neural network structure based on multiresolution learning is put forward, and the studies of network weights adopt damped least squares.
文中重点研究了数字高程模型的小波变换简化以及构建多分辨率数字模型中LOD简化技术并进行试验应用。
In the paper focal point was put on the model simplification with wavelet transform and the construction of multi-resolution model with LOD technology and at the same time trial was applied.
在数字图像小波多分辨率分析理论基础上，采用小波变换方法对高分辨遥感图像的目标地物边缘进行信息增强，然后与多光谱遥感图像进行特征信息融合。
After the wavelet's multi-resolution analysis, a feature fusion approach was adopted to enhance remote sensing image edge and improve the definition and resolving power of the image.
通过对采集的振动信号进行小波多分辨率分析和FFT谱分析，得出被测结构振动响应包含的各频率对应的振动波形曲线。
Through wavelet analysis and FFT analysis to the collected structure vibration signal, the vibration wave curves and analysis results of different frequencies are acquired.
同时利用了小波变换的多分辨率性质，以渐近分辨率的方式压缩图片，具有分辨率可扩展性。
In addition, by exploiting the multi-resolution property of wavelet, the scheme that is resolution-scaleable can compress the transformed image for progressive resolution.
小波变换提供了一种图像的多分辨率分解重建的表示形式，这种小波分解能够有效的利用人类视觉系统的特性压缩图像。
Wavelet provides a compact multi-resolution representation and reconstruction of image, which makes it possible to exploit the property of Human Visual System for image coding.
小波变换具有多分辨率和多尺度特性，特别适合于二维图像信号的处理，目前已应用在静止图像的压缩标准中。
While wavelet transform is suitable in image compression due to its multi-resolution and multi-scale analysis property, and is used in the standards of image compression.
噪声的存在是图像分割的困难所在，本文着重研究了基于小波变换的多分辨率分割中噪声抑制的问题。
Suppressing noise is the difficult problem in image segmentation, so we have study suppressing noise in multiresolution segmentation based on Wavelet transform.
提出了对传感器采集到的微弱信号进行累加平均和小波变换中的多分辨率分析方法相结合去噪。
The method that combine the cumulative average and multi-resolution analysis in wavelet transform was presented which can de-noise the weak signal collected from the sensor.
文中研究了简单的图像融合方法、基于多尺度塔形分解的多分辨率图像融合方法和基于小波变换的图像融合方法。
The simple image fusion method, the multiresolution image fusion techniques based on multiscale pyramid decomposition (MPD), and the image fusion method based on wavelet transform are studied.
依据信号与噪声的小波变换在不同分辨率下呈现不同特性的特点，提出了多分辨率支集图像低通滤波方法。
Multiresolution support for lowpass filtering is introduced according to different property of wavelet transform for signal and noisy at different scale.
提出一种基于二进小波变换与多层分组神经网络的自由手写体数字的多分辨率识别算法。
In this paper, a new scheme of multiresolution recognition of unconstrained handwritten numerals based on dyadic wavelet transform and multilayer cluster neural network is presented.
针对小波变换多分辨率边缘检测中单一阈值难以区分边缘与噪声的问题，本文提出了一种自适应的阈值方法，并改进了边缘链接方法。
To discern edge and noise in multiresolution edge detection used single threshold, we put forward a kind of adaptive threshold and improve the method of edge linking.
良好的局部放大特性和多分辨率学习特性使得小波神经网络比神经网络有更强的自适应能力、更快的收敛速度和更高的预报精度。
The good local amplification and multi-resolution characteristic make the wavelet network have strong adaptive capacity, fast convergence speed and high precision of prediction.
本文基于小波变换具有多尺度多分辨率分析的优点，提出了在特定的小波变换分频瞬时属性上，利用局部结构熵算法来检测地震数据的局部不连续性。
Local structural entropy measure in frequency division is put forward to detect local discontinuities of seismic data, by the virtue of the instantaneous attributes based on wavelet transform.
本文提出一种新的多分辨率纹理分类方法，该方法采用称为小波帧的冗余小波分解，从而获得具有稳定性和平移不变性的特征描述。
The method adopts redundant wavelet, which is called wavelet frame, to decompose and then to achieve the characteristic description of stability and translational constancy.
小波分解对信号做多分辨率分解，可以突出信号的特征信息，便于QRS波群检测。
The wavelet transform does multi-resolution analysis on the signal which clarifies the electrocardiogram (ECG) signal characteristics to more easily detect the QRS complex.
为了达到多尺度分频解释的目的，本文将小波多分辨率分析应用到相干体提取过程中。
In order to attain the goal of using multi scale frequency divided data for interpretation, the paper applied the wavelet multi resolution analysis to detect the coherent data volume.
首先基于小波多分辨率分析方法将负荷序列分解成具有不同频率特征的序列。
Firstly, based on wavelet multi-resolution analysis method, the load serials are decomposed to different sub-serials which show the different frequency characteristics of the load.
本算法利用小波变换的多分辨率特性来进行图象的小波域分解，这样可以获得更好的图象保真度并且比在空域中的水印嵌入算法更稳健。
The multiresolution structure of wavelet is used to construct the image frequency components., which has better image fidelity preservation and robustness than spatial domain based techniques.
在传统图像灰度方差评价函数的基础上，利用小波多分辨率分析，提出了一种新的自动聚焦算法。
On the basis of evaluation function of using image intensity variance, we proposed a new auto-focusing algorithm by means of Wavelet Transform Multi-Resolution Analysis(WTMRA) theory.
然后运用基于小波多分辨率数据组合的文字水印方法对博物馆数字图像进行了版权保护应用研究，并对数字水印图像进行了稳定性测试，取得了较好的效果。
Study of copyright of digital image in museum by wavelet multi solution data combination and study of stability of the dig ital display make a better result.
而小波变换多分辨率分解的优良特性，既能大幅度的压缩图像数据，又能很好的保留图像的绝大部分的信息。
The wavelet has the good multi-resolution decomposition features, which both have a significant compression of image data, but also retain most of the information of an image.
提出一种基于正交基函数的小波神经网络设计方法，采用多分辨率学习确定隐含层结构，并用收敛较快的阻尼最小二乘法训练权值。
In this approach the network structure is determined by multiresolution learning, and the weights are trained by damped least squares which has fast convergent rate.
根据小波多分辨率分析和水文序列的统计自相似性，提出了水文序列分形维数的小波估计方法，给出了其计算步骤。
Based on the statistical self-similarity of hydrolgy time series, a new approach for estimating the fractal dimension by using successive wavelet transform coefficients is proposed.
实验结果表明，小波变换的多分辨率分析对于分析处理具有时变谱特性的非平稳信号是一种新的有效方法。
Experiments show that the multiresolution analysis of wavelet transform is an effective new method for processing unstable signals having time variant spectra.
算法充分利用连续小波变换探测信号奇异性的能力和小波的多分辨率特性。
The new algorithm mainly recurred to the ability of detecting singularity in signal by continuous wavelet transform and multi-resolution analysis of wavelet transform.
算法充分利用连续小波变换探测信号奇异性的能力和小波的多分辨率特性。
The new algorithm mainly recurred to the ability of detecting singularity in signal by continuous wavelet transform and multi-resolution analysis of wavelet transform.
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