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AGuidetoMATLAB
英文版的MATALB入门教材，剑桥大学出版社(A Guide to MATLAB for Beginners and Experienced Users- B.R.Hunt,R.L.Lipsman,J.M.Rosenberg- (Cambridge University Press))
- 2010-07-08 20:27:46下载
- 积分：1
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Neural_network_Matlab
一个用Matlab写的BP神经网络的应用实例，设备检查用。(Written in Matlab using a BP neural network application examples, device-examine.)
- 2010-01-12 00:03:20下载
- 积分：1
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SA_Sw
模拟退火算法应用程序在图像方面的应用，供初学者参考(Simulated annealing applications to the application of the image, information for beginners)
- 2010-12-08 16:54:36下载
- 积分：1
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texture
preservation of fine details in the images
- 2011-05-14 00:19:04下载
- 积分：1
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MdoernSignalProcess
包含了多个信号处理的算法，多通道滤波器，小波变换等信号处理的算法(filters, wavelets)
- 2009-10-17 16:39:25下载
- 积分：1
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assem
Assembel element matrices Ke ( and fe ) into the global stiffness matrix K ( and the global force vector f ) according to the topology matrix edof.
- 2009-05-29 22:53:25下载
- 积分：1
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2D-FDTD
时域有限差分法的2维代码~~~~很详细的，大家可以看看~~~~(Finite-difference time-domain 2 dimensions of the code
)
- 2010-12-21 17:34:45下载
- 积分：1
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OFDM_occour
OFDM信号通过功率放大器以及功率放大器的预失真全套代码(OFDM PA)
- 2021-04-06 18:19:02下载
- 积分：1
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K-meanCluster
How the K-mean Cluster work
Step 1. Begin with a decision the value of k = number of clusters
Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following:
Take the first k training sample as single-element clusters
Assign each of the remaining (N-k) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster.
Step 3 . Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample.
Step 4 . Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments. (How the K-mean Cluster workStep 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (Nk) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3. Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4. Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments.)
- 2007-11-15 01:49:03下载
- 积分：1
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matlab
数字信号处理及其MATLAB实现，详细介绍了数字信号处理的原理和过程，并给出详细的MATLAB实现程序。(Digital signal processing and MATLAB realization of digital signal processing described in detail the principles and processes, and gives a detailed implementation program MATLAB.)
- 2009-11-25 22:11:33下载
- 积分：1
