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1)  orthogonal multi distinguish analysis
正交多分辨分析
2)  orthonormal component discriminant analysis
正交分量辨别分析
3)  multiresolution analysis
多分辨分析
1.
Linear prediction based on wavelet multiresolution analysis;
基于小波多分辨分析的线性预测
2.
Image recognition based on moment and multiresolution analysis;
基于矩和多分辨分析的图像识别
3.
Eigenvalue problem of an integral equation and multiresolution analysis;
积分方程的特征值问题和多分辨分析
4)  multi-resolution analysis
多分辨分析
1.
Deriving gas hold-up values from pressure signals in slurry beds by multi-resolution analysis method;
从浆态床压力脉动信号中辨识气含率的多分辨分析方法
2.
A simplified split-merge image segmentation method based on multi-resolution analysis;
一种基于多分辨分析的简化的分裂-合并图像分割算法
3.
The jump omen extraction method of fault signal based on multi-resolution analysis;
多分辨分析在信号突变征兆提取中的应用
5)  Multi Resolution Analysis
多分辨分析
1.
Mallat fast decomposition algorithm based on multi resolution analysis is introduced.
介绍基于多分辨分析的Mallat快速小波分解算法。
2.
The continuous wavelet transform definition, multi resolution analysis and Mallat fast decomposition algorithm are introduced.
介绍了连续小波变换定义、多分辨分析及Mallat快速小波分解算法。
3.
This paper presents a unified framework of signal using polynomial spline basis functions and wavelets, and gives some special cases of spline functions and wavelets, and deduces the fast analysis/synthesis pyramid algorithm on the basis of multi resolution analysis of L 2 .
介绍了多项式样条函数及样条小波的统一表达式 ,并给出了几种具有特殊性质的样条函数及小波 ,同时根据 L2空间多分辨分析的定义推导出样条的分解 /综合快速塔式算法。
6)  MRA
多分辨分析
1.
To increase the accuracy of the short-term power load forecasting,in this paper,the wavelet transform(WT) based on Multi-resolution Analysis(MRA) is applied to decompose short-term power load sequence into wavelet component.
为提高电力系统短期负荷预测准确度,首先利用多分辨分析的小波变换对短期电力负荷序列进行分解处理,根据其在小波各尺度上子序列的特性分别进行回归预测,再将预测结果进行小波重构,得到了满意的预测结果。
2.
Using Mallat algorithm on the basis of wavelet transform and multiresolution analysis(MRA) in connection with traditional FFT,a new speech signal fundamental frequency detection method is presented.
将基于小波变换与多分辨分析 (MRA)下的Mallat算法与传统的快速傅立叶变换(FFT)相结合 ,提出了一种新的语音信号的基音频率检测方法。
3.
In the paper,the low-frequency information which reflects the trend of stock price change is extracted using wavelet MRA and the Mallat method,and the time of stockjobbing is analyzed.
本文利用小波多分辨分析及快速Mallat算法提取反映股价基本变化趋势的低频信息,并分析了证券交易的时机选择。
补充资料:高分辨电子显微镜(见高分辨电子显微术)


高分辨电子显微镜(见高分辨电子显微术)
high resolution electron microscope

高分辨电子显微镜high resolution eleetronmieroseope见高分辫电子显微术。
说明:补充资料仅用于学习参考,请勿用于其它任何用途。
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