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Simulink2
动态系统建模方法介绍,学习怎样实现用MATLAB对非线性动态系统的建模(Simulink MATLAB)
- 2010-08-25 14:48:39下载
- 积分:1
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bss_eval
一种bss盲源信号分离的工具包 可以用于盲信号的提取(a blind source separation of the tool kit can be used for Blind Signal Extraction)
- 2007-04-29 16:52:43下载
- 积分:1
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wuxianchuangandingwei
无线传感定位的一个入门算法,介绍了信标节点密度与定位精度的关系(Wireless sensor positioning as an entry algorithm introduced beacon node density and the relationship between positioning accuracy)
- 2011-09-23 22:41:28下载
- 积分:1
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gequ
matlab 制作歌曲 最炫民族风 满天都是小星星等(matlab produce songs coolest Ethnic twinkle little star)
- 2012-11-21 20:30:54下载
- 积分:1
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Modulation
BPSK, QPSK, 16-QAM Modulation Mapping BER in communication
- 2010-12-22 13:15:17下载
- 积分:1
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matlab-help
说明: matlab help,很不错的教程,对你一定会有帮助(GOOD)
- 2010-04-15 08:34:36下载
- 积分:1
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fixed23-old
solution of matlab project based on numercal methods
- 2010-12-06 05:01:07下载
- 积分:1
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GaBp
用GA训练BP网络的权值、阈值从而优化神经网络(GA training BP network with the right value, the threshold in order to optimize the neural network)
- 2009-05-24 18:03:52下载
- 积分:1
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project
Advanced Digital Signal Processing project
- 2013-07-31 16:37:19下载
- 积分:1
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src-fusion
A. Fusion at the Feature Extraction Level
The data obtained from each sensor is used to compute a
feature vector. As the features extracted from one biometric
trait are independent of those extracted from the other, it is
reasonable to concatenate the two vectors into a single new
vector. The primary benefit of feature level fusion is the
detection of correlated feature values generated by different
feature extraction algorithms and, in the process, identifying a salient set of features that can improve recognition accuracy
[14]. The new vector has a higher dimension and represents the
identity of the person in a different hyperspace. Eliciting this
feature set typically requires the use of dimensionality
reduction/selection methods and, therefore, feature level fusion
assumes the availability of a large number of training data.
- 2013-03-14 16:40:42下载
- 积分:1