-
the-bootstrap-filtering
关于粒子滤波基本算法以及改进型的实例仿真，适合初学者对粒子滤波算法的学习(On the basic algorithm and improved particle filter instances of simulation, suitable for beginners to learn on the particle filter)
- 2011-08-17 22:55:13下载
- 积分：1
-
Fm_modulation_and_demodulation
调频信号调制解调fm_modulation_and_demodulatin(FM signal modulation and demodulation fm_modulation_and_demodulatin)
- 2008-12-13 13:13:04下载
- 积分：1
-
Verzani-SimpleR
This book is verzari simple R programm. I think this book is really helpful.
- 2010-11-30 06:55:10下载
- 积分：1
-
jiancechengxu
角点检测的一个MATLAB源代码，希望对初学者有点帮助。(corner detection of a MATLAB source code, and I hope to be useful to beginners.)
- 2007-06-01 13:45:26下载
- 积分：1
-
CDMA-Authentication
Motorola CDMA Authentication Introduction
- 2014-09-13 09:16:39下载
- 积分：1
-
package
可进行短时平均能量，短时平均幅度，短时平均过零率，短时自相光，短时傅里叶变换的函数,使用方便，(The average energy can be short-term, short-term average rate, the average short-term zero-crossing rate, short-term autocorrelation of light, short-time Fourier transform of the function, easy to use,)
- 2011-10-07 09:21:44下载
- 积分：1
-
m-files
system identification, m document based on idetification
- 2013-11-23 22:38:54下载
- 积分：1
-
AVL
Implementation of an AVL tree using C. A data structure type.
- 2014-01-09 03:18:41下载
- 积分：1
-
rnnsim
RNNSIM ver. 1.0 is a program with an intercative graphical user interface
(GUI) that runs under MATLAB ver. 5.0 or higher. The program can be used
in training and testing the Random Neural Network(RNN) models.
This version (ver. 1.0) implements only the 3 layer feed forward RNN model.
In the next versions, the multi hidden layers and the recurrent RNN models
can be implemented. To obtain faster training, the training section can be
written as a MEX file and invoked from the GUI.
If you have the m files in the directory rnnsim for example, then you can
run the program following the next steps:
1- run MATLAB as usual
2- from the MATLAB command window, write cd rnnsim
3- from the MATLAB command window, write rnnsim
- 2010-03-04 16:55:55下载
- 积分：1
-
SEKSGUI0.65
this code was development by George christakos, Serre, M and Patrick Bogaert for implement the Bayesian Maximun Entropy Approach to enviromental and physical mapping research
- 2013-11-08 23:39:33下载
- 积分：1
