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ljf_chaoliujisuan_090326
正确的潮流计算程序,经多个算例验证了正确性,值得一看(Calculation of trend right by a number of examples to verify the correctness, see)
- 2009-03-29 09:49:27下载
- 积分：1
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hechengjilu
一个合成记录，可以生成特定反射系数和特定条件下的合成地震记录。(A synthetic seismogram, can generate a specific reflection coefficient and the specific conditions of the synthetic seismogram.)
- 2009-06-13 14:40:04下载
- 积分：1
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myBeamforming
阵列信号处理中的常规波束形成。
原创。。。。。。。。(Array signal processing in conventional beamforming. Original. . . . . . . .)
- 2010-10-30 09:44:25下载
- 积分：1
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OMP
二维图像的omp算法重构，使用matlab 编程(The 2-d image reconstruction omp algorithm using matlab programming,)
- 2011-05-14 08:39:51下载
- 积分：1
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ship-recognition
matlab的程序，可用来进行船型识别。包括图像预处理，特征提取，船型识别三个方面。(matlab program can be used to identify the ship. Including image preprocessing, feature extraction, ship identification three aspects.)
- 2014-09-18 09:51:12下载
- 积分：1
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New-Folder-(3)
this code shows the new filter application ........................................
- 2012-08-20 16:35:32下载
- 积分：1
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Sigmon-K.-MATLAB-Primer-(3rd-ed.-1993)(en)(34s)
The purp ose of this Primer is to help you b egin to use MATLAB. It is not intendedto b e a substitute for the User s Guide and Reference The purpose of this Primer is to help you begin to use Matlab.The Primer can best be used hands-on. You are encouraged to work at the computer as you read thePrimer and freely exp eriment with examples. This Primer, along with the on-line helpfacility, usually suce for students in a class requiring use of MATLAB
- 2011-12-03 04:32:04下载
- 积分：1
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chap4
matlab图像处理实例详解——数字图像的运算(matlab image processing example explanation- digital image computing)
- 2013-11-06 14:22:20下载
- 积分：1
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RBF神经网络隐层采用标准Gaussian径向基函数
自己编写RBF神经网络程序，RBF神经网络隐层采用标准Gaussian径向基函数，输出层采用线性激活函数，其中数据中心、扩展常数和输出权值均用梯度法求解，它们的学习率均为0.001。其中隐节点数选为10，初始输出权值取[-0.1，0.1]内的随机值，初始数据中心取[-1，1]内的随机值，初始扩展常数取[0.1，0.3]内的随机值，输入采用[0 1]的随机阶跃输入(Write your own RBF neural network, RBF neural network hidden layer using standard Gaussian radial basis function, the output layer using a linear activation function, the data center, and the output weights are constant expansion with the gradient method, the learning rate is 0.001. The number of hidden nodes is 10, the initial output value [-0.1, random value of 0.1], initial data center [-1, random value of 1], the initial expansion constant of [0.1, a random value within 0.3], using a random order [0 1] step input)
- 2017-09-24 20:33:56下载
- 积分：1
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noma
说明： energy efficiency of noma
- 2020-03-07 13:56:24下载
- 积分：1
