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dqpsk
四进制差分相移键控(键控调制方法)，樊昌信《通信原理》内容(Four M-ary differential phase shift keying (keying modulation method), Fan Changxin " Communication Theory" content)
- 2009-03-19 22:56:09下载
- 积分：1
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quotient
商图像 减少光照影响 可用于人脸识别的图像预处理(Business image recognition can be used to reduce illumination of the image preprocessing)
- 2011-05-27 16:33:26下载
- 积分：1
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matlabstudy
精通matlab综合辅导与指南，doc文档，matlab学习的辅导资料(Proficient in matlab comprehensive counseling and guidance, doc documents, matlab learning counseling information)
- 2010-06-05 16:32:51下载
- 积分：1
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MyLS
最小二乘法Matlab编程实现//最小二乘法Matlab编程实现(Least Squares Matlab Programming
Least Squares Matlab Programming
)
- 2010-12-25 17:02:23下载
- 积分：1
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MOPSO-Iran
PSO program for microgrid
- 2018-02-12 01:20:57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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ofdm_fading_new
在高斯与一径瑞利衰落信道下对OFDM系统（QPSK调制）的功率普的仿真(in Gaussian with a Rayleigh fading channel right OFDM system (QPSK) Pu Power Simulation)
- 2007-05-27 00:27:38下载
- 积分：1
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matlab-hundun
混沌的演示，关于matlab做混沌模型的初步的一些介绍和详解(Chaos demo on matlab to do some initial chaos model introduction and explain)
- 2013-11-27 15:17:31下载
- 积分：1
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MATLAB-
《MATLAB 神经网络30个案例分析》程序和数据(The MATLAB neural network analysis of 30 cases programs and data
)
- 2015-01-22 15:10:28下载
- 积分：1
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MOMEDA+Teager（MCKD+Teager）
说明： 能够实现对实验数据的降维，为故障分类做准备(It can reduce the dimension of experimental data and prepare for fault classification)
- 2021-04-16 10:08:53下载
- 积分：1
