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smobyclick
helpful code to mooths data by clicking on the figure
- 2010-09-29 19:16:51下载
- 积分：1
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matlab-base
matlab的讲义，一些基础知识，语法知识等等(matlab lectures, some basic knowledge, grammar, etc.)
- 2011-11-11 14:28:30下载
- 积分：1
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AntOptimization
Ant Optimization algorithm
- 2013-12-17 00:27:36下载
- 积分：1
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5
说明： 这是一篇关于基于图像序列的人体步态识别方法研究的文章(This is a sequence of image-based recognition of human gait article)
- 2010-05-06 19:12:58下载
- 积分：1
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ASSIGNMENT
digital communication codes
- 2012-05-19 18:48:13下载
- 积分：1
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Robust-Control-Toolbox
MATLAB鲁棒控制工具箱，详细介绍工具箱的应用及实例讲解。(MATLAB Robust Control Toolbox, detailing the toolbox applications and examples to explain.)
- 2012-06-27 22:20:56下载
- 积分：1
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JPDA
在运动的位置叠加噪声。进行JPDA概率数据关联及kalman滤波。
两运动目标在x-y平面做匀速直线运动。初始位置是（4000,1200）（300,1500）速度分别是（200,200）（400,200）传感器对量目标进行位置状态量测。
采样间隔T=1,点数n=80.检测概率为1，正确量测落入跟踪内的概率为0.99，杂波均匀分布的密度为2个/km2由RAND函数产生在[0，1]上均匀分布的随机变量，跟踪门限为9.21。
(Superimposed noise in the position of the movement. JPDA probabilistic data association and kalman filtering. Two moving targets uniform linear motion in the xy plane. The initial position (4000,1200) (300,1500) speed (200,200) (400,200) position sensor on the amount of target state measurements. Sampling interval T = 1, points n = 80. Detection probability of correctly measured fall into the tracking probability 0.99, 2/km2 clutter uniform distribution of density generated by the RAND function [0,1] uniformly distributed random variables tracking threshold of 9.21.)
- 2021-04-26 20:18:45下载
- 积分：1
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bpsk_ofdm_commtoolbox
i am in need 4g related matlab code.i learning in area of lte-advanced downlink for writing the matlab code
- 2014-10-12 23:48:24下载
- 积分：1
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bilinear
In this paper, we introduce a new machine-learning-based data classification algorithm that is applied
to network intrusion detection. The basic task is to classify network activities (in the network log
as connection records) as normal or abnormal while minimizing misclassification. Although different
classification models have been developed for network intrusion detection, each of them has its strengths
and weaknesses, including the most commonly applied Support Vector Machine (SVM) method and the
Clustering based on Self-Organized Ant Colony Network (CSOACN). Our new approach combines the SVM
method with CSOACNs to take the advantages of both while avoiding their weaknesses. Our algorithm is
implemented and evaluated using a standard benchmark KDD99 data set. Experiments show that CSVAC
(Combining Support Vectors with Ant Colony) outperforms SVM alone or CSOACN alone in terms of both
classification rate and run-time efficiency.
- 2013-12-21 13:40:52下载
- 积分：1
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0100000069_supp
with development of embedded adaptive controllers for mimo scheduling.
- 2014-02-25 14:59:33下载
- 积分：1
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