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arithmetic2
Data Compression Arthmetic Algorithm Example.
Tested in Python 2.7
just run py file
- 2013-12-09 21:23:39下载
- 积分:1
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CSO
一个好用的鸡群算法程序,供新手学习使用,可在网上找相关资料(A good CSO program,for beginners to learn and use,,you can find relevant information online.)
- 2018-05-29 14:44:22下载
- 积分:1
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VC_Matlab
通过MATLAB引擎,利用VC开发MATLAB,包括一个自己开发的小程序和一片word文档资料(Through the MATLAB engine, developed by VC MATLAB, including its own development programs and a small word document data)
- 2011-08-27 23:31:12下载
- 积分:1
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math2
The Communications Blockset is a collection of Simulink® blocks for designing
and simulating communications systems. With the Communications Blockset,
you can design models in the form of block diagrams, using simple
click-and-drag mouse operations. You can run simulations on a model at the
push of a button, and change parameters while the simulation is running.
- 2009-10-21 23:43:14下载
- 积分:1
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xuexi
用于初步学习智能算法的同学,是]标准PSO 的一种演绎出的又一好的算法(yes,it is very good for study matlab.if you want study it,if you need it ,please download it.)
- 2011-01-12 23:19:00下载
- 积分:1
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Matlab2010
经典超强教程(清晰、免费版),matlab入门,进阶(Classic Super tutorial (clear, free version), matlab entry, advanced)
- 2015-04-23 04:19:48下载
- 积分:1
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fcmGUI
用Matlab写的FCM算法,包括GUI界面的设计,实现模糊聚类功能。(FCM algorithm is written using Matlab, including the GUI interface design, implementation, fuzzy clustering functionality.)
- 2021-02-25 15:09:38下载
- 积分:1
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S-MAc
说明: 关于无线传感器网络的S-MAC定位算法的C 语言代码.希望对大家有帮助.(Wireless sensor networks on S-MAC algorithm for C language code. Want to help you.)
- 2009-08-21 21:08:45下载
- 积分:1
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voice_activity_detection
说明: 关于语音信号端点检测的有用文献,主要介绍了关于端点检测的有关技术和方法(Endpoint detection of speech signals useful literature are introduced on the endpoint detection of the techniques and methods)
- 2010-04-17 16:54:24下载
- 积分:1
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RICE-UNIVERSITY
标准压缩感知(CS)理论决定了可靠的信号恢复是可能给M= O(KLOG(N / K))的测量。我们证明了它可以通过利用超越简单的稀疏性和可压缩性由包括价值观和信号系数的位置之间的依赖关系更加逼真信号模型大大降低Mwithout牺牲的鲁棒性。(The standard compressive sensing (CS) theory dictates that robust signal recovery is possible from M=O(Klog(N/K)) measurements. We demonstrate that it is possible to substantially decrease Mwithout sacrificing robustness by leveraging more realistic signal models that go beyond simple sparsity and compressibility by including dependencies between values and locations of the signal coefficients.
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- 2014-01-06 20:07:54下载
- 积分:1