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SAX_2006_ver
SAX比其他符号算法更简便、高效 在符号化过程中实现了减维降噪 ,保证在符号空间计算出的两个符号序列距离满足实际两个时间序列距离的下界要求 ,即不会出现漏报(SAX (Symbolic Aggregate approXimation))
- 2013-12-01 00:35:21下载
- 积分：1
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face
基于matlab的人脸识别程序 (Face recognition program based on MATLAB)
- 2013-05-23 17:28:57下载
- 积分：1
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huanrezhanmohukongzhi
基于PLC编写的换热站模糊控制水温的程序，适用欧姆龙的编程软件打开(PLC-based preparation temperature heat transfer station fuzzy control procedures for Omron programming software to open)
- 2014-06-26 16:27:48下载
- 积分：1
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check_cpty
对一个给定的状态转移矩阵求其联合分布矩阵，联合熵，平均互信息量以及共熵。可以画出平均互信息量的曲线(For a given state transition matrix of their joint distribution matrix, the joint entropy, mutual information and the average total entropy. Can draw the curve of the average mutual information)
- 2011-12-12 08:57:30下载
- 积分：1
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TextView-marquee-they-scroll
textview跑马灯，自己滚动
TextView marquee they scroll
- 2014-01-26 15:18:23下载
- 积分：1
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integrated navigation
以捷联惯性导航系统为主，添加里程计、卫星成为组合导航的半实物仿真程序(integrated navigation)
- 2020-12-25 09:09:04下载
- 积分：1
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distance_classify
function g=distance_classify(A,b)
距离判别法程序。
输入已分类样本A（元胞数组），输入待分类样本b
输出待分类样本b的类别g
注：一般还应计算回代误差yita
输入已知分类样本的总类别数n 每类作为元胞数组的一列(function g = distance_classify (A, b) from the Criterion procedures. Input samples have been classified A (cell array), the importation of samples for classification b output samples for classification g categories b Note: the calculation should also be back on behalf of the general error input yita of the total known types of classification of the number of samples n each Cellular-type array as a)
- 2009-05-09 17:15:44下载
- 积分：1
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as
说明： 74154中文资料.doc 74154中文资料.doc
- 2010-05-08 21:16:33下载
- 积分：1
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rtejfgds
现有的代数特征的抽取方法绝大多数采用一维的方法，即首先将图像转换为一维向量，再用主分量分析（PCA）,Fisher线性鉴别分析（LDA）,Fisherfaces式核主分量分析（KPCA）等方法抽取特征，然后用适合的分类器分类。针对一维方法维数过高，计算量大，协方差矩阵常常是奇异矩阵等不足，提出了二维的图像特征抽取方法，计算量小，协方差矩阵一般是可逆的，且识别率较高。(existing algebra feature extraction method using a majority of the peacekeepers, First images will be converted into one-dimensional vector, and then principal component analysis (PCA), Fisher Linear Discriminant Analysis (LDA), Fisherfaces audits principal component analysis (KPCA), and other selected characteristics, then use the appropriate classification for classification. Victoria against an excessive dimension method, calculation, covariance matrix is often inadequate singular matrix, a two-dimensional image feature extraction method, a small amount of covariance matrix is usually reversible, and the recognition rate higher.)
- 2020-08-14 13:28:28下载
- 积分：1
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yinzibiao-(2)
根据输入的电路矩阵表示形式，形成节点导纳矩阵，形成因子表的过程可以看做是规格化运算和消去运算的重复过程，重复的次数和非基准点的节点个数相同。
每个过程中进行的操作都相同，首先，存储规格化因子及消去因子；其次，对本行进行规格化运算，并将其值存储在因子表中；然后，对其后的每行进行消去运算；如此循环n次得到因子表。(Representation of the input of the circuit matrix, forming a node admittance matrix formation process can be seen as a factor table normalization process operations and eliminate duplicate operations, the same number of nodes and the number of repetitions of non-reference point. Each operation carried out during the same, first of all, storage and elimination factor normalization factor secondly, the Bank normalized operations, and its value is stored in the factor table then, each row will be erased after their operation so the cycle n times to get factor table.)
- 2014-12-14 18:56:22下载
- 积分：1
