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BCH_malab
说明： 用于生成BCH码的生成多项式和最小多项式的malab代码，以及伴随式的计算表达式(BCH code used to generate the generation polynomial and minimal polynomial of malab code, as well as the calculation with the expression)
- 2009-07-29 11:29:29下载
- 积分：1
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Carrier-aggregation-
LTE-A系统中载波聚合介绍，初学者适合理解其概念(Carrier aggregation for LTE-advanced mobile communication systems.pdf)
- 2013-12-24 15:09:54下载
- 积分：1
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mg2D
二维贝叶斯反演方法的实现matlab代码，包含地质统计学知识(The realization of two-dimensional Bayesian inversion method matlab code, including geostatistics knowledge)
- 2021-03-19 20:49:19下载
- 积分：1
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CC2480
开发人员指南 接口电路 仿真设计 软件编程指南(Download from ti)
- 2010-05-25 00:55:45下载
- 积分：1
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svpwm-pmsm-dq
svpwm仿真模型，以及基于svpwm的矢量控制模型。(svpwm simulation models, as well as vector control model based svpwm.)
- 2014-11-26 20:11:29下载
- 积分：1
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Example1
ANSI input 5p1 implementation example
- 2012-10-23 14:09:32下载
- 积分：1
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802.11aOFDMbyMATLAB
很完善的一个OFDM仿真程序,它以FUNCTION的形式,再现了OFDM映射,IDFTDFT,同步(时间频率同步)和信道估计,以及频率偏移的估计等一系列代码.(very sound one OFDM simulation program, which is in the form FUNCTION, Reproduction of OFDM mapping, IDFTDFT, synchronous (time-frequency synchronous) and channel estimation, and the estimated frequency offset a series of code.)
- 2006-10-22 03:27:22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
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oap3
最优波束形成的方法（包括谱加权，阵列多项式和z变换、波束空间的方向采样、最大最小设计等）(optimun array processing )
- 2012-04-23 10:23:58下载
- 积分：1
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kruskal
algorytm kruskala w matlabie
- 2010-06-01 03:20:54下载
- 积分：1
