登录
首页 » matlab » MOD

MOD

于 2013-03-11 发布 文件大小:6KB
0 111
下载积分: 1 下载次数: 2

代码说明:

  MODULATOR MIMO IS VERY GOOD REFERENCE

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • 4
    说明:  用Jacobi和Gauss-seidel方法解方程组。并比较迭代次数,是误差小于10E-3(Use of Jacobi and Gauss-seidel method to solve equations. And compare the number of iterations is less than 10E-3 error)
    2010-08-26 21:11:21下载
    积分:1
  • HW4
    EKF+UKF滤波算法在汽车做二维运动中的应用(The EKF+ UKF filtering algorithm in two-dimensional movement in the car)
    2012-03-20 16:35:34下载
    积分:1
  • siscod
    LS and MMSE comparaison
    2010-05-25 18:00:21下载
    积分:1
  • facail-recognition-based-on-BP
    基于BP神经网络的人脸识别系统的研究 采用的是PCA和BP网络(Based on BP neural network face recognition system using PCA and BP Neural Network)
    2012-05-18 18:33:48下载
    积分:1
  • Linear-Prediction
    Linear Prediction using Levinson Durbin Recursion and Lattice Filters
    2013-02-12 09:28:09下载
    积分:1
  • Sample1_VerySimple
    it is a very good example for OFDM which has tow CP removal Technic.
    2015-04-07 10:42:13下载
    积分:1
  • longgekuta
    隆格库塔程序 大家一定会用得到的 可以分享下(Longgekuta program you will get to share with the next)
    2010-05-21 21:25:58下载
    积分:1
  • forward-algorithm.m
    马尔科夫链,马尔科夫一阶算法,隐马尔科夫算法(forward algorithm)
    2012-05-17 12:34:30下载
    积分:1
  • motor-control
    this file is a simulink file about dc and ac motor control
    2011-09-03 06:14:40下载
    积分:1
  • RVM_matlabToolBox
    相关向量机(RVM)的matlab源程序,包含快速算法,内含代码使用说明。 RVM采取是与支持向量机相同的函数形式稀疏概率模型,对未知函数进行预测或分类。 优点: (1) 不仅仅输出预测目标量的点估计值,还可以输出预测值的分布. (2) 使用更少数量的支持向量,从而显著减少输出目标量预测值的计算时间. (3) RVM不需要估计过多的参数. (4) RVM对是否满足Mercer 定理的核函数没有限制,适应性更好(Relevance Vector Machine (RVM) of the matlab source code, including fast algorithm that contains code for use. RVM support vector machine is taken the same functional form sparse probabilistic model to predict the unknown function or classification. Advantages: (1) is not only the amount of output predicted target point estimates, but also the distribution of predicted values ​ ​ can be output. (2) using a smaller number of support vectors, thereby significantly reducing the output target amount predicted value calculation time. (3) RVM does not require excessive parameter estimation. (4) RVM meets Mercer theorem on the kernel function is not limited, and better adaptability)
    2013-11-21 11:05:48下载
    积分:1
  • 696518资源总数
  • 104225会员总数
  • 32今日下载