-
great-lib
operate the library on windows operation
- 2014-08-21 14:22:55下载
- 积分:1
-
SolveStOMP
经典的压缩感知cs重构算法之一分级omp(The classic one compressed sensing reconstruction algorithm cs cs omp)
- 2010-06-07 17:28:17下载
- 积分:1
-
PSOSET
this file contains some m-files about calculating the fractional fourier transform
- 2010-10-24 18:06:39下载
- 积分:1
-
Holubowicz119325
matlab - how to draw a map with DEM file on plot :)
- 2012-05-19 22:40:43下载
- 积分:1
-
two-energy-band
运用matlab绘制能带。可以有效地提高绘图的效率和减少误差(matlab point picture)
- 2013-03-07 09:48:39下载
- 积分:1
-
Desktop
200 THz electric field modulated by Gaussian envelope
- 2010-05-17 20:49:56下载
- 积分:1
-
chaosa1
参考变分不等式的混沌搜索算法 赵 晖,高自友(北京交通大学交通运输学院,北京100044)(Reference variational inequality chaos search algorithm ZHAO Hui, GAO Zi-you (Beijing Jiaotong University, Transportation Institute, Beijing 100044))
- 2009-11-19 13:56:54下载
- 积分:1
-
watfill
说明: 这是matlab上实现的一个注水算法的程序。(This is a matlab algorithm to achieve a water injection program.)
- 2010-04-04 19:23:45下载
- 积分:1
-
LMS
最小均方濾波器是一類可通過最小化誤差訊號之均方值而修正濾波器係數,以類比所需理想濾波器的自適應濾波器,其中作為修正依據的誤差訊號為理想參考訊號與實際輸出訊號之差。該種濾波器所用之最小均方法只以當前之訊號誤差值為準進行修正,是一種隨機梯度下降法。最小均方法係由斯坦福大學的Bernard Widrow教授及他的首位博士班學生Marcian Hoff於1960年提出。最小均方濾波器屬於常見的自適應濾波器種類之一。(The minimum mean square filter is an adaptive filter that can correct the filter coefficients by minimizing the mean square value of the error signal to analogize the desired ideal filter. The error signal used as the correction reference is the ideal reference signal and the actual output. The difference between the signals. The minimum averaging method used in this kind of filter is only corrected based on the current signal error value, which is a stochastic gradient descent method. The minimum mean method was proposed in 1960 by Professor Bernard Widrow of Stanford University and his first PhD student, Marcian Hoff. The least mean square filter is one of the common types of adaptive filters.)
- 2019-02-21 22:43:06下载
- 积分:1
-
SpaceCarving
nice file to read and have a nice syllabus
- 2010-12-03 03:26:16下载
- 积分:1