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Description: 介绍了两通适滤波器组的完全重构条件，利川E uc lidean分解算法，将两通适滤波器组的设计问题简化为
寻找给定特性的低通滤波器的最佳Euclidean }I_补滤波器的单变量非线性优化问题，并探讨了采川遗传算法设计此
类高度非线性优化问题最后通过设计例子说明将遗传算法应川到滤波器组的设计，是可行的
-Abstract: T his paper f>resenLs un effe< Live rneLhod based on genetic ulgoriLhrn for designing Lw<r < hunnel perfe< L re< orr
sLru< Lion(PPS) filler banks. After Lhe perfe< L re<onslru<:Lion(PPS) conditions are studied, Lhe design f>rol>lem is simf>lified
Lo seur< h for Lhe best eu< lideun <ornf>lernenLurv-filler uwresf>onding Lo Lhe given low-puss filler by using Eu< lideun fu< Lor-
izuLion. Then genetic ulgoriLhrn is used Lo <x>rnpuLe Lhe nonlinear f>rogrumming fwl>lern. Finullv un exumf>le is given Lo i1-
lusLruLe Lhe proE>osed rneLhod is effe< Live.
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Size: 62464 |
Author: 百度 |
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Description: 思路简要说明：
1、图像二值化
将图片中的各点用0或1表示，1为有效点，0为背景。这里使用的是最大类间方差法
（otsu），在资料中有介绍。
2、去除干扰点
3、分割
将整个的图片分为每个单独的字，在下一步中才能一一识别。
4、与样本库进行对比，寻求最近似匹配
这步是比较核心的地方，由于要识别的图形每次都是随机变化的，我们不能进行完
全匹配识别，所以使用的是‘欧氏距离’来进行最近似匹配，资料中的《自由手写体
数字识别》里面有详细说明。
（样本库文件是按照匹配的特征通过事先编写的程序进行学习得到的）
该识别思路对目前很多验证码有效，识别速度快，正确率基本还可以（在一定程度内
样本量越大正确率越高），不能识别的情况也不少，比如字符粘连，导致程序无法正确
分割，从而识别失败，有朋友介绍神经网络识别方法不错，有空一定要学习下。-A brief description of ideas:
1, image binarization
Pictures of all the points expressed by 0 or 1, 1 for the effective point, 0 for background. Used here is the largest between-class variance
(Otsu), are introduced in the data.
2, removal of interference points
3, partition
The whole picture is divided into each individual character, in the next step in order to identify 11.
4, compared with the sample database, the search might match the recent
This step is to compare the core places, due to the recognition of each of the graphics changes are random, we can not be finished
Identification of the entire match, so the use of the Euclidean distance to be like the recent match, the information in the "free handwritten
Digital Identification, "which is described in detail.
(Sample library features in accordance with the matching pre-prepared through the process of learning to be)
The identification of a lot of ide
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Size: 874496 |
Author: yangq |
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Description: 本程序设计了一个有限域类，可以提供GF(P)[P为素数]上的矩阵运算，特别通过欧几里德算法提供了多项式的有限域矩阵逆运算。-This procedure designed a type of finite fields can be GF (P) [P for prime] on matrix calculation, in particular through the Euclidean algorithm provides a finite field polynomial matrix inverse operation.
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Size: 1024 |
Author: 小陈 |
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Description: A novel texture-based Automatic Fingerprint Authentication System (AFAS) is proposed. A fingerprint image is preprocessed to enhance the image by Short Time Fourier Transform (STFT) analysis. Then, three sets of invariant moment features, as a kind of texture features, are extracted from three different sizes of Region of Interest (ROI) areas based on the reference point from the enhanced fingerprint image. Each set of invariant moments contain seven invariant moments. Fingerprint verification is realized by Euclidean distance between the two corresponding features of the test fingerprint image and template fingerprint image in the database
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Size: 276480 |
Author: joyce |
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Description: CVAP includes 4 External validity indices, 14 Internal validity indices and 5 clustering algorithms (K-means, PAM, hierarchical clustering, SOM and etc.). It supports other clustering algorithms via loading a solution file with class labels, or by adding new codes. And similarity metrics of Euclidean distance and Pearson correlation coefficient are supported.-CVAP includes 4 External validity indices, 14 Internal validity indices and 5 clustering algorithms (K-means, PAM, hierarchical clustering, SOM and etc.). It supports other clustering algorithms via loading a solution file with class labels, or by adding new codes. And similarity metrics of Euclidean distance and Pearson correlation coefficient are supported.
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Size: 258048 |
Author: tra ba huy |
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Description: 用Euclidean算法实现BCH的编码和译码，仿真可直接运行-BCH encode and decode
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Size: 4096 |
Author: 王丽 |
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Description: 我的毕业设计，用matlab编的关键帧提取的代码，参考了光流法的代码。是基于帧差的欧式距离，均值，方差，差异系数下的关键帧提取。代码调试通过，运行结果理想，与大家分享下。-I graduated from design, matlab key frame extraction for the code, with reference to code optical flow method. Frame difference is based on the Euclidean distance, the mean, variance, difference coefficient under the key frame extraction. Debugging through the code, run the results are satisfactory, the next to share with you.
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Size: 3506176 |
Author: 刘月 |
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Description: 代码用于图形图像的像素点欧几里得距离计算转换等工作-Code for the graphic image of the Euclidean distance-based pixel conversion, etc.
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Size: 16743424 |
Author: 李林 |
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Description: In this project we have processed the speech signal with the help of the DIGITAL SIGNAL PROCESSING techniques. The speech signal is given as the input will be verified using speech recognition technique using matlab. We have used Mel Frequency Cepstral Coefficient (MFCC) along with Vector Quantization (VQLBG) and Euclidean Distance to identify different characters. Based on the results, data was send to Parallel Printer Port of the computer & using relay different devices will be controlled.
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Size: 2048 |
Author: SimonKap22 |
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Description: extended euclidean algorithm for polynomials with maple
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Size: 10240 |
Author: hasan |
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Description: function in R software to calculate 36 clusterings of a data matrix (clusterings are in columns), using hierarchical average, cosine, centroid and single linkages, pam and neural gas and applying the Euclidean distance to the data.
Clusterings can be combined using a Cluster Ensemble.
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Size: 1024 |
Author: muti |
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Description: Java applet that allows to create a customised spatial data set for clustering, by clicking with the mouse in a panel. Data coordinates appear in the right box and a matrix of Euclidean/ cosine distances between the points can be calculated by selecting the corresponding button at the top frame. Values can be copied directly from the applex boxes or check the java virtual machine console in the navigator.
the applet is called mouse_click35.java
the calling html code is test14.html
you can execute the applet online in:
http://it.e-technik.uni-ulm.de/~amalgs/data_generator/test14.html
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Author: muti |
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Description: 通过欧几里德距离对三维空间内的数据点进行聚类：
从文件读入三列表示坐标的数据进行聚类。按项目总数和组数平均划分。首先计算两两之间的距离，选出最近的两个点，再按距离由小到大排序，找出距这两个点最近的若干个点。
除去这些点后对其余的点重复进行上述操作。-By Euclidean distance on three-dimensional space, clustering of data points: from the file read into the three coordinates of the data indicated that cluster. According to the average number of total number of projects and group division. First, calculate the distance between 22 to elect the nearest two points, and then from small to large order to identify these two points away from a number of recent points. After removing these points the rest of the point of repeating to carry out such operations.
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Size: 2048 |
Author: 陈雷 |
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Description: 小波变换在信号处理、图像处理、模式识别、计算机视觉等
方面广泛应用。本文提出了一种基于Haar小波的时问序列相似
模式匹配模型．它首先对时间序列数据进行Haar小波变换．以
降低数据的维度。首先将所要查询的时间序列进行降维，也就是
对时间序列数据进行小波变换，对序列进行标准化131，得到降维
之后的小波序列．这样可以得到系数子集的良好近似采用尺度
序列表示原始序列．并将其看成多维空间中的一个点，通过计算
两序列差的平方和的平方根作为这两个时间序列的距离函效
(即欧氏距离)。用小波变换保持了局部性质。而欧氏距离就是要
判断相似性的距离函数．所以当在作完变换之后。通过低频分量
来压缩数据，成功的计算出实际距离的下界。如果计算的结果小
于一个由用户所定义的门槛值．则认为这两个时问序列是相似
的。
在-Of wavelet transform in signal processing, image processing, pattern recognition, computer vision, etc.
Aspects of wider application. In this paper, Haar wavelet-based time series similarity
Pattern matching model. It is first time-series data, Haar wavelet transform. To
To reduce the data dimension. Will first want to check the time series dimension reduction, that is,
Pairs of time series data using wavelet transform, standardize the sequence 131, to be reduced-
After the wavelet sequence. This can be a good approximation coefficients of a subset of the use of scale
Sequence indicated that the original sequence. And to treat it as a multi-dimensional space a point, by calculating the
Two sequences and the square root of the square of the difference as the distance between these two time series letter effect
(Ie, Euclidean distance). Maintained with the local nature of the wavelet transform. The Euclidean distance is to
To determine simila
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Author: lx |
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Description: 摘要：拐点是数字图像中的一个重要信息载体 提出一种新的拐点检测算法 该算法并非寻找连续空间中曲率的离散近似计算方法，而是源于离散曲线的外观特征，推导出离散曲线上拐点处k个点对间欧氏距离平方和局部最小这一重要性质。基于该性质，本算法首先利用Freeman链码的性质.过滤掉物体边界上明显不可能成为拐点的象素，然后在剩余的边界点中通过寻找该局部最小值定位出拐点。给出了本算法与四种著名拐点检测算法的对比实验。
-Abstract: The inflection point is a digital image of an important information carrier put forward a new turning point detection algorithm the algorithm does not look for continuous space discrete approximation of the curvature calculation method, but from the appearance of characteristics of discrete curve derived discrete curve the inflection point at k-points between the squared Euclidean distance and the local minimum of this important property. Based on the nature of the algorithm is the first to use Freeman chain code in nature. Filter out objects clearly can not become a turning point on the border pixel, and then in the remaining boundary points by finding out the turning point of the local minimum position. The algorithm is given inflection point detection algorithm with the four well-known comparison of experiment.
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Author: changhe.cheng |
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Description: classify the objects in data matrix based on the attributes
Criteria: minimize Euclidean distance between centroids and object points
For more explanation of the algorithm-classify the objects in data matrix based on the attributes
Criteria: minimize Euclidean distance between centroids and object points
For more explanation of the algorithm
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Size: 1024 |
Author: jntu |
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Description: simple grid interpolation of scatter data by using euclidean distance. Colouring z with different RGB and save in ASCII, comma delimeter-simple grid interpolation from scatter data.
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Size: 7168 |
Author: Chen |
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Description: 一、 本程序采用16QAM调制方式，对一串2进制信源进行调制，用升余弦滚降函数进行基带调制，再调到高频信道；在信道上加入高斯白噪声，运用匹配滤波器解调，画出解调星座图，运用最小欧氏距离译码判决，计算误比特率。-First, this program uses 16QAM modulation mode, for a string of two binary source is modulated with a raised cosine roll-off function for base-band modulation, and then transferred to high-frequency channel in the channel by adding Gaussian white noise, the use of matched filter device demodulator, draw demodulation constellation, using the minimum Euclidean distance decoding decision, calculate bit error rate.
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Author: zhaoyang |
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Description: 进一步解决基于互信息的配准算法在配准精度、速度和误配率之间的相互制约问题。提出一种新的配准参数搜索策略——三级配准，将平移、旋转参数分开搜索；在分析互信息配准的优点和局限性的基础上，将模糊理论中的欧几里德贴近度引入三级 配准过程中。实验结果表明，本文提出的配准策略在保持基于互信息配准精度不变的情况下，迭代步数、配准时间和误配率均有明显改善。-Further resolve the mutual information based registration algorithm in the alignment accuracy, speed, and mismatch between the rate of mutual constraints. A new registration parameter search strategy- 3 registration, would be translation and rotation parameters of separate search in the analysis of mutual information registration of the advantages and limitations, based on the fuzzy theory in the Euclidean close 3 to introduce a registration process. Experimental results show that the proposed alignment strategy for maintaining the mutual information based registration accuracy of the same circumstances, the iteration step number, registration time and the error distribution rate showed significant improvement.
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Author: arechi |
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Description: 用带形状校正的腐蚀膨胀实现Euclidean距离变换-Implementation of Euclidean Distance Transforms Using Erosion and Dilation with Form Correction
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Size: 552960 |
Author: 陆宗骐 |
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