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Win32GUI
windows gui wrapper for fb
- 2013-12-12 15:44:33下载
- 积分：1
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MyFftTest
实现快速傅里叶变换的控制台程序，对用户输入的数组做变换。(Fast Fourier transform console program, to an array of user input to make change.)
- 2015-02-07 11:19:03下载
- 积分：1
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huatu
VC调用MATLAB的简单事例，没有复杂的功能，只适合初学者(A simple example of calling MATLAB VC)
- 2011-08-09 15:15:53下载
- 积分：1
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iHMM
infinite HMM
Refer to Beal s Paper
Applying Gibbs Sampling in inference
the number of states of HMM is changeable in this algorithm, based on Dirichlet Proce(infinite HMMRefer to Beal s PaperApplying Gibbs Sampling in inferencethe number of states of HMM is changeable in this algorithm, based on Dirichlet Proce)
- 2008-01-24 10:10:54下载
- 积分：1
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gongetidu
共轭梯度法的matlab实现，给出任意的一个对称矩阵，可通过较小的迭代次数得到所要求精度的数值解(Conjugate gradient method matlab to achieve, given any symmetric matrix by a smaller number of iterations to obtain the required accuracy of the numerical solution)
- 2012-11-12 21:37:19下载
- 积分：1
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UTF-8
字符编码之间的转换解决中文字符的显示问题(A character encoding conversion between Chinese character display problem)
- 2014-10-29 20:08:31下载
- 积分：1
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ecg
qrs波算法，一个用maltab写的简单的算法。确定q,r,s的位置。(ECG SIMULATION USING MATLAB)
- 2010-03-05 21:36:09下载
- 积分：1
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Multi2Carrier-Measurements
利用GNSS 进行高精度导航定位的前提是正确固定载波相位观测值的整周模糊度。由Galileo 系统的4 个载波观测值可以
形成诸多有良好特性的组合观测值,利用这些组合观测值,结合MCAR 方法,可以有效地确定整周模糊度。(The use of high-precision GNSS navigation and positioning the premise is correct carrier phase observations fixed integer ambiguity. May consist of four carriers observations Galileo system
There are many good characteristics to form a combination of observations using a combination of these observations, combined with MCAR method can effectively determine the integer ambiguity.)
- 2013-12-21 14:07:20下载
- 积分：1
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xinxilun
这是信息论里的知识，有循环编码、香农编码、费诺编码的程序(This is the knowledge in the information theory, a cycle encoding, shannon coding, coding procedure fee)
- 2014-11-20 22:39:24下载
- 积分：1
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LMS
1,、设置变量和参量：
X(n)为输入向量，或称为训练样本
W(n)为权值向量
e(n)为偏差
d(n)为期望输出
y(n)为实际输出
η为学习速率
n为迭代次数
2、初始化，赋给w(0)各一个较小的随机非零值，令n=0
3、对于一组输入样本x(n)和对应的期望输出d，计算
e(n)=d(n)-X^T(n)W(n)
W(n+1)=W(n)+ηX(n)e(n)
4、判断是否满足条件，若满足算法结束，若否n增加1，转入第3步继续执行(, set the variables and parameters:
X (n) is the input vector, otherwise known as the training sample
W (n) for the weight vector
e (n) for the deviation
d (n) is the desired output
y (n) is the actual output
η is the learning rate
n is the number of iterations)
- 2011-12-10 20:22:05下载
- 积分：1
