-
mv
说明： machine vision 工具箱，一直都在用，做机器视觉参考(machine vision toolkit has been used, so machine vision reference)
- 2007-04-19 17:07:19下载
- 积分：1
-
MATLAB-program-in-common-use
matlab的一些常用算法程序集，包括微分，插值等等，对初学者很实用(matlab assembly of some commonly used algorithms, including differential, interpolation, etc., very useful for beginners)
- 2011-07-06 11:17:54下载
- 积分：1
-
DTW-based-on-0~9
一个语音识别程序，运用VQ算法，样本已经存在与文件夹中，点击test.m就可直接运行，调试完全。(A speech recognition program, using the VQ algorithm, the sample has been existing and folder, click on the test.m can be run directly, debugging.)
- 2013-03-07 20:44:47下载
- 积分：1
-
Nonlinear-Fiber-Optics
基于AGRAWAL, G. P. (2001). Nonlinear Fiber Optics (3rd ed.)中求解分布傅里叶变换解非线性薛定谔方程(Based AGRAWAL, GP (2001). Nonlinear Fiber Optics (3rd ed.) The Fourier transform of the distribution solution for solving the nonlinear Schrodinger equation)
- 2014-10-20 17:48:14下载
- 积分：1
-
important
mimo系统容量的描述，注水算法，用于下一代移动通信领域(Description mimo system capacity, water algorithm for next-generation mobile communications)
- 2014-02-25 08:53:28下载
- 积分：1
-
dsp_yxp_3
说明： matlab开发函数，一些简单的例子和数字滤波器设计函数(matlab development function, some simple examples and digital filter design function)
- 2011-04-14 09:42:58下载
- 积分：1
-
A-Dtest
A-D检验 本文是关于A-D检验的MATLAB程序，适用于序言A-D检测的同学，希望参考指正(AD test article is on the AD test MATLAB program, students apply to the preamble to AD detection, correct me want to refer to)
- 2012-06-15 18:32:50下载
- 积分：1
-
iradon
matlab关于iradon变换。matlab关于iradon变换。matlab关于iradon变换。(Matlab on the iradon transform.Matlab on the iradon transform.Matlab on the iradon transform.)
- 2014-12-02 11:31:26下载
- 积分：1
-
matlab_xianxingguihua
基于matlab的线性规划计算，有两个简单的算例，非常适合初学者(The calculation is based on linear programming matlab, there are two simple examples, very suitable for beginners)
- 2014-12-09 12:47:03下载
- 积分：1
-
fit_ML_log_normal
fit_ML_normal - Maximum Likelihood fit of the laplace distribution of i.i.d. samples!.
Given the samples of a laplace distribution, the PDF parameter is found
fits data to the probability of the form:
p(x) = 1/(2*b)*exp(-abs(x-u)/b)
with parameters: u,b
format: result = fit_ML_laplace( x,hAx )
input: x - vector, samples with laplace distribution to be parameterized
hAx - handle of an axis, on which the fitted distribution is plotted
if h is given empty, a figure is created.
output: result - structure with the fields
u,b - fitted parameters
CRB_b - Cram?r-Rao Bound for the estimator value
RMS - RMS error of the estimation
type - ML
- 2011-02-09 19:07:30下载
- 积分：1
