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LevelSet
国外牛人写的一个多水平集目标分割算法,文件中同时还包含了几篇国外水平集算法的文章，对于像了解水平集的人来说，有很大用处
(multi-Level set method)
- 2014-10-24 15:50:28下载
- 积分：1
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QAM2rayleigh
4qam调制信号通过瑞利信达的matlab仿真(4qam modulated signal by Rayleigh up matlab simulation)
- 2013-04-25 21:59:43下载
- 积分：1
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koch_snow
你可以绘制生长代数=n的koch雪花~~~~~~~~~~~~~~~~~~~~~~~~~~~(You can plot koch snow of the growth generation = n )
- 2011-12-27 23:11:16下载
- 积分：1
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NCUT
此程序是谱聚类中，经典的Ncut算法。用matlab编写的。(This program is spectrum clustering, classic Ncut algorithm.The program
uses matlab。)
- 2012-03-05 21:28:01下载
- 积分：1
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HC
说明： 半车动力学模型，可用于动力学分析，用于分析垂向激励与整车响应的关系(half car dynamics model)
- 2018-05-21 13:46:51下载
- 积分：1
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pcm
通过MATLAB工具箱对pcm的13折线法量化编码译码过程仿真(MATLAB toolbox pcm by 13 line coding and decoding process simulation method to quantify)
- 2010-11-05 15:40:36下载
- 积分：1
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S_DBWebApplication1
S_DBWEbapplication 实例 作为例子参考 讲解演示器作用(S_DBWEbapplication instance as an example to explain the reference to the role of presenter)
- 2013-11-25 22:25:51下载
- 积分：1
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旅行商问题
说明： 使用蚁群算法解决旅行商问题，求路径最短问题(Using ant colony algorithm to solve the traveling salesman problem and find the shortest path)
- 2020-06-10 10:52:31下载
- 积分：1
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MSRCRbyZhang
带色彩恢复的多尺度视网膜增强算法（MSRCR）的原理、实现及应用。
(Multi-scale recovery of the retina with color enhancement algorithms (MSRCR) principle, implementation and applications.)
- 2013-12-07 21:26:37下载
- 积分：1
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Laplace
传统的短时谱估计语音增强算法通常假设语音谱分量相互独立，没有考虑语音谱分量间的相关性。针对这
一问题，该文提出一种新的基于多元Laplace分布模型的短时谱估计算法。首先，假设语音的离散余弦变换(DCT)
系数服从多元Laplace分布，以此利用谱分量间的相关性；在此基础上，利用多元随机矢量的高斯尺度混合模型表
示，推导得到语音DCT系数矢量的最小均方误差(MMSE)估计的解析表达式；并进一步推导了基于该分布模型的
语音存在概率，对最小均方误差估计子进行修正。实验结果表明，该算法在抑制背景噪声和减少语音失真等方面优
于传统的语音增强方法。(The spectral components of speech are usually assumed to be independent in traditional short-time
spectrum estimation, which is not the case in practice. Tosolve this problem, a new speech enhancement algorithm
with multivariate Laplace speech model is proposed in this paper. Firstly, the speech Discrete Cosine Transform
(DCT) coefficients are modeled by a multivariate Laplace distribution, so the correlations between speech spectral
components can be exploited. And then a Minimum-Mean-Square-Error (MMSE) estimator based on the proposed
model is derived using a Gaussian scale mixture representation of random vectors. Furthermore, the speech
presence uncertainty with the new model is derived to modify the MMSE estimator. Experimental results show
that the developed method has better noise suppression performance and lower speech distortion compared to the
traditional speech enhancement method. )
- 2014-01-18 10:44:40下载
- 积分：1
