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OFDM_simulation_system
OFDM通信系统仿真模型
包括编码，调制，IFFT，上下变频，高斯信道建模，FFT，PAPR抑制，各种同步，解调和解码模块
最后验证了系统设计的可靠性
是通信理论OFDM技术仿真实例(OFDM communication system simulation models, including coding, modulation, IFFT, and down conversion, Gaussian channel model, FFT, PAPR suppression, various synchronization, demodulation and decoding module final validation of the reliability of the system design is communication theory simulation OFDM technology)
- 2010-12-11 15:38:02下载
- 积分：1
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test1
水果图像识别，利用MATLAB进行图形的特征提取，边缘检测，阈值分割等(Fruit and image recognition, the use of MATLAB for graphics feature extraction, edge detection, thresholding, etc.)
- 2011-05-22 10:46:04下载
- 积分：1
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ImageEdgeDetection_segmentation_matlab
说明： 边缘提取源码，国内一高手写的，对计算机视觉等很有用，代码精炼(Edge source, the domestic one written by a master of computer vision and other useful code Refining)
- 2008-11-17 10:37:03下载
- 积分：1
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Matlabyichuansuanfa
遗传算法工具箱的简介及其使用 遗传算法工具箱的简介及其使用 遗传算法工具箱的简介及其使用(Introduction to Genetic Algorithm Toolbox and its use)
- 2010-10-23 11:37:09下载
- 积分：1
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1
说明： 边射直线阵天线波束方向图演示程序 直线阵最常见的工作模式(Broadside linear array antenna beam pattern demo linear array of the most common mode of)
- 2010-10-26 14:48:06下载
- 积分：1
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spec_plot
用matlab打开即可，可以绘制功率谱的函数，十分方便(using Matlab can be opened, the power spectral mapping function, which is very convenient)
- 2006-11-19 23:06:40下载
- 积分：1
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singleround
matlab绘制图形，绘制圆形双心圆以及圆环。(matlab draw graphics, draw the circular double heart round ring)
- 2013-03-07 10:01:28下载
- 积分：1
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chen
混沌chen系统的仿真代码，用预估校正法编写(Chaos chen system simulation code, written in predictor-corrector method)
- 2012-04-05 20:55:16下载
- 积分：1
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sy1
简单抽样函数，没有什么特别用处，最基础的matlab应用(Simple sampling function, no special use, application of the most basic matlab)
- 2011-06-20 08:52:30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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