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Mfsk
实现mfsk的仿真 最近做的课程设计的内容 很难啊 郁闷(The realization of the simulation MFSK recent content of the curriculum design is difficult ah depressing)
- 2007-12-02 13:05:11下载
- 积分：1
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adc3
take a input vector which is no of users of b[kx1] and
code vector which will be a matrix now s=[Nxk],where
then give to matched filter,non-correlating detector,
by randomised sequence.
- 2009-11-15 03:43:32下载
- 积分：1
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LinearprogrammingandnetworkflowsBazaraa
Linearprogrammingandnetworkflows Bazaraa
- 2010-12-27 00:04:52下载
- 积分：1
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xwdock2.02beta
matlab coding for developing image fusion toolkit
- 2011-01-19 20:50:32下载
- 积分：1
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Track
一些matlab中很有用的源码程序，对于初学者学习很有帮助(matlab )
- 2010-05-14 17:09:41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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Codes-Source
loading a text file from a directory to your workspace in matlab
- 2009-04-17 23:15:13下载
- 积分：1
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usingcontrol
matlab控制系统工具箱。一系列经典控制学问题在matlab中的实现(control system toolbox for use with matlab.Examples for control analysis in matlab are given)
- 2012-10-12 02:19:03下载
- 积分：1
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robotics7
Robotics kinematics, Matlab program for serial Robot.
- 2015-03-17 12:00:54下载
- 积分：1
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co00c
adaptive control mrac
- 2012-01-24 20:16:29下载
- 积分：1
