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Electromagnetic-Field-2D
ANSYS电磁场分析指南，有关2D的分析。(ANSYS electromagnetic field analysis guidelines for the 2D analysis.)
- 2013-07-31 15:48:01下载
- 积分：1
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eigen-eigen-6e7488e20373.tar
国外的一个用C实现的类似matlab数学库，功能貌似很强大，很多功能已经有源码了，喜欢C语言的人有福了。(Foreign matlab math library in C, the function looks like a very powerful, many functions have been source of the Blessed are those who like the C language.)
- 2012-06-06 22:23:02下载
- 积分：1
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Assignment_message_Decoding
Use of basic signal processing tools to decode an OFDM message
- 2013-03-02 20:42:54下载
- 积分：1
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HS_VaR_Backtest
Plain Historical Simulation Back-testing Result
- 2013-09-28 22:27:15下载
- 积分：1
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Simpson
Simpson二重积分数值算法，注释比较详细(Simpson double integral numerical algorithm, the Notes in more detail)
- 2008-12-27 03:47:46下载
- 积分：1
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Matlab_xiaobo
说明： 关于小波变换的代码，希望对大家有帮助，同时希望能找到自己需要的代码(On wavelet transform code, we would like to help, at the same time hoping to find that they need the code)
- 2008-10-21 09:24:22下载
- 积分：1
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GroupSparseBox_V2
Approximate Greedy Solutions to the problem min||x(k)||_2,0 such that Ax = b
- 2009-09-12 23:34:06下载
- 积分：1
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ofdmmatlab5
ofdm matlab implementation details
- 2009-04-06 18:51:05下载
- 积分：1
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speed
说明： 基于matlab的多速率信号处理程序，希望对大家有帮助。(Matlab-based multi-rate signal processing procedures, we hope to help.)
- 2006-04-29 18:12:05下载
- 积分：1
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fecgm
独立成份分析（ＩＣＡ）以及ｗｉｎｎｅｒ滤波 Source separation of complex signals with JADE.
Jade performs `Source Separation in the following sense:
X is an n x T data matrix assumed modelled as X = A S + N where
o A is an unknown n x m matrix with full rank.
o S is a m x T data matrix (source signals) with the properties
a) for each t, the components of S(:,t) are statistically
independent
b) for each p, the S(p,:) is the realization of a zero-mean
`source signal .
c) At most one of these processes has a vanishing 4th-order
cumulant.
o N is a n x T matrix. It is a realization of a spatially white
Gaussian noise, i.e. Cov(X) = sigma*eye(n) with unknown variance
sigma. This is probably better than no modeling at all...( Source separation of complex signals with JADE.
Jade performs `Source Separation in the following sense:
X is an n x T data matrix assumed modelled as X = A S+ N where
o A is an unknown n x m matrix with full rank.
o S is a m x T data matrix (source signals) with the properties
a) for each t, the components of S(:,t) are statistically
independent
b) for each p, the S(p,:) is the realization of a zero-mean
`source signal .
c) At most one of these processes has a vanishing 4th-order
cumulant.
o N is a n x T matrix. It is a realization of a spatially white
Gaussian noise, i.e. Cov(X) = sigma*eye(n) with unknown variance
sigma. This is probably better than no modeling at all...)
- 2010-05-27 23:08:51下载
- 积分：1
