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PUMA-nonlinear-control
MATLAB/SIMULINK BASED
NON Linear Control of PUMA 560
- 2014-12-12 04:04:09下载
- 积分：1
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false_position
false_position method - use a root in polynomial or function / iterative method
- 2011-12-13 20:09:23下载
- 积分：1
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J6_2012--Kalman-interpolation
卡尔曼滤波器进行信道估计的一篇文章，适用于OFDM-MIMO系统。(Kalman filter for channel estimation in an article for OFDM-MIMO systems.)
- 2013-12-22 20:53:26下载
- 积分：1
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Demo_MWC
该程序是基于Eldar论文仿真用于实现MWC(This package is used to simulate the Modulated Wideband Converter in MATLAB)
- 2020-10-06 10:27:39下载
- 积分：1
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about_Communication_Fundamentals_in_my_side
总结了自己关于通信原理学习的一下认识,希望大家多交流(about Communication Fundamentals in my side)
- 2010-09-24 20:06:01下载
- 积分：1
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DOA
线形阵列DOA估计的CBF Capon MUSIC ESPRIT ML算法的matlab源代码(this file includes matlab codes of CBF MUSIC Capon ESPRTI and ML algorithm for DOA estimation )
- 2012-03-29 17:43:35下载
- 积分：1
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matlabforarrayprocessing
用于阵列信号处理的常用代码
包括经典处理和自适应处理
代码准确无误都能运行
可读性强(matlab code for array processing)
- 2021-04-29 10:38:43下载
- 积分：1
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a
说明： 该资料用于学习matlab界面编程，对于初学者可以达到事半功倍的效果，能快速入门(The information is used to learn the matlab interface programming for beginners can achieve a multiplier effect, to Quick Start)
- 2013-04-03 10:59:21下载
- 积分：1
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kriging
kriging代理模型 进行近似计算的 可以自行改变参数(kriging surrogate model to approximate calculation can change the parameters)
- 2020-12-17 15:39:11下载
- 积分：1
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SRGTSToolbox
说明： SURROGATES工具箱是一个多维函数逼近和优化方法的通用MATLAB库。当前版本包括以下功能：
实验设计：中心复合设计，全因子设计，拉丁超立方体设计，D-optimal和maxmin设计。
代理：克里金法，多项式响应面，径向基神经网络和支持向量回归。
错误和交叉验证的分析：留一法和k折交叉验证，以及经典的错误分析（确定系数，标准误差;均方根误差等;）。
基于代理的优化：高效的全局优化（EGO）算法。
其他能力：通过安全裕度进行全局敏感性分析和保守替代。(SURROGATES Toolbox is a general-purpose MATLAB library of multidimensional function approximation and optimization methods. The current version includes the following capabilities:
Design of experiments: central composite design, full factorial design, Latin hypercube design, D-optimal and maxmin designs.
Surrogates: kriging, polynomial response surface, radial basis neural network, and support vector regression.
Analysis of error and cross validation: leave-one-out and k-fold cross-validation, and classical error analysis (coefficient of determination, standard error; root mean square error; and others).
Surrogate-based optimization: efficient global optimization (EGO) algorithm.
Other capabilities: global sensitivity analysis and conservative surrogates via safety margin.)
- 2020-04-20 22:30:13下载
- 积分：1
