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selection_diversity
说明: 接收端选择性多样化,用于优化瑞丽信道的衰落,减少误码率(selection diversity)
- 2011-03-16 22:19:41下载
- 积分:1
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Chapter-8-of-the-matlab-data-fitting
matlab中的第8章 数据拟合(包含例子和程序源码)(Chapter 8 of the matlab data fitting (including examples and program source code))
- 2013-12-23 12:17:40下载
- 积分:1
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cdma-matlab
CDMA系统的matlab仿真代码CDMA系统的matlab仿真代码(Matlab simulation code CDMA systems)
- 2010-10-22 18:56:19下载
- 积分:1
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CyclicCode
基于Matlab的循环码的编码与译码,内附源码的详细注释及其编译码的过程(Matlab code based on the cycle of encoding and decoding, containing detailed notes and source coding and decoding process)
- 2010-05-27 11:56:38下载
- 积分:1
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Signals-and-SystemsAnalysis-and-threalization-of-M
1. 该光盘包含了“信号与系统分析及MATLAB实现”一书的第八章所有程序;
2. 为了方便读者阅读程序,所有程序均采用中文注释。MATLAB的程序编辑器不支持中文显示,用户只需在Word下直接打开源程序文件,即可阅读程序中的中文注释;
3. 程序文件的命名分为以下三种类型:
(1) 若为书中例题的程序,则程序文件名一律以ex开头,后面跟4位数字(前两位表示章号,后两位表示例题序号)表示的该程序所在例题的编号。例如,ex0603.m是例6.3的程序,而ex1102.m则是例11.2的对应程序。
(2) 若为书中图形的实现程序,则程序文件名一律以figure开头,后面跟4位数字(前两位表示章号,后两位表示图形序号)表示的该程序所绘图形的编号。例如,figure1203.m是实现图12.3的程序,而figure0710.m则是实现图7.10的对应程序。
(3) 若为函数文件,则直接以函数名命名,例如文件sconv.m即是书中函数sconv()的对应程序。
()
- 2008-06-06 11:38:38下载
- 积分:1
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LocalLinearApproximation
Local Linear ApproximationLocal Linear ApproximationLocal Linear Approximation
- 2010-12-14 00:49:10下载
- 积分:1
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CHAPTER2
说明: 利用MATLAB编写先进PID控制程序,使得控制效果更好,达到良好动态效果(MATLAB prepared using advanced PID control procedures, making better control to achieve good dynamic effects)
- 2008-11-30 09:35:58下载
- 积分:1
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DVB_S2
Cycle slip probability of the phase unrapping algorithm(Cycle slip probability of the phase unrapp ing algorithm)
- 2006-11-02 11:15:08下载
- 积分:1
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level_fuzzy
liquid level control using fuzzy logic controller
- 2014-09-07 06:17:04下载
- 积分:1
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MTKLjcxhyanz
NTKL法可以同时检测光谱异常点、参考数据异常点及其他们共同的异常点,该方法的基本思路是基于蒙特卡洛采样,随机将样本集划分为校正集与预测集,用校正集建模,并对没参与建模的样本进行预测误差计算,进行几千次这样随机采样,每个样本点都可得到其预测误差分布。如果奇异样本在校正集中,整个模型的质量将受到影响;相反,如果奇异样本在预测集中,仅此样本的预测结果受到影响。(NTKL method can simultaneously detect abnormal spectrum and abnormal reference data points and their common abnormal point, the basic idea of this method is based on the monte carlo sampling, sample set random be divided into calibration set and prediction set, using correction modeling, modeling and participated in the samples of the prediction error calculation, a thousands of times that of random sampling, each sample point can be obtained the prediction error distribution.If singular samples in correction, the model of quality will be affected.Singular samples in predicting concentration, on the contrary, if only for the sample prediction results are affected.)
- 2016-07-15 10:36:52下载
- 积分:1