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cordic_atan
CORDIC arctangent(atan) Simulink model. You can generate HDL from this model
- 2011-01-16 02:00:10下载
- 积分：1
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compeletion
将三维图像分割为由3*3*3体素组成的立方体实现更细化的分析(The three-dimensional image is divided by 3* 3* 3 cube of voxels composition to achieve a more detailed analysis)
- 2014-12-29 18:19:39下载
- 积分：1
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wlan_11n_simulink_mod
Simulink model of wlan.11.n
- 2010-05-16 00:50:35下载
- 积分：1
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matlab_2
ANOTHER BOOK OF METLAB WITH LOT OF EXERCISES
- 2014-09-23 15:33:53下载
- 积分：1
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Model
Model of induction machine
- 2014-12-17 22:50:27下载
- 积分：1
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difference
finite difference method solving one dimensional advection-diffusion equation
- 2011-04-20 21:02:22下载
- 积分：1
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GA-of-genetic-algorithms
遗传算法原理及应用 遗传算法的基础应用，是遗传算法的基本知识(Principle and Application of genetic algorithm based on genetic algorithm applications, basic knowledge of genetic algorithms)
- 2011-05-07 17:03:15下载
- 积分：1
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3Easy-Small-Cell-Backhaul--Feb-2012
3Easy Small Cell Backhaul LTE基站回传设备介绍。(3Easy Small Cell Backhaul Feb 2012.rar)
- 2015-04-02 22:49:24下载
- 积分：1
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linear_system_identification.tar
The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order (The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order)
- 2008-08-03 10:18:16下载
- 积分：1
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application-of-CG-and-Gauss-Seidel-
共轭梯度法和Gauss-Seidel迭代法的matlab实现，实例操作，取得了良好的效果(Conjugate gradient method and the Gauss-Seidel iteration method matlab implementation, instance operations, and achieved good results
)
- 2011-10-07 20:29:03下载
- 积分：1
