-
chardiv
说明: 利用BP神经网络进行字符识别的系统源码,能进行有效数字字符识别。(BP neural network Character Recognition system source code, can be effective digital character recognition.)
- 2006-02-28 19:19:23下载
- 积分:1
-
DSSS1
基于matlab的直序扩频通信系统仿真模型(Matlab-based direct-sequence spread spectrum communication system simulation model)
- 2011-07-22 15:09:38下载
- 积分:1
-
tivaapps-master
Tiva C 123 Application projects
- 2014-11-05 09:29:58下载
- 积分:1
-
junzhilvbonmd
MATLAB对数字信号进行均值滤波,尤其是对数字图像(MATLAB for digital signals mean filter, especially for digital images)
- 2014-02-22 18:43:06下载
- 积分:1
-
DOA
基于自相关或四阶累计的music和esprit算法的DOA估计(一维)(Based on autocorrelation or fourth-order cumulant of music and esprit algorithm for estimating DOA (one-dimensional))
- 2021-04-27 22:38:44下载
- 积分:1
-
DDA-receiver
分别给出了带卷积吗,卷积吗-RS吗,RS吗的系统误码率仿真程序( )
- 2013-04-29 15:32:17下载
- 积分:1
-
mokh-simul
simulation for equlizer
- 2012-12-02 06:14:04下载
- 积分:1
-
keystone-demo
基于keystone算法的距离迁徙校正,用于SAR成像中插值运算(Migration distance keystone correction algorithm for SAR imaging interpolation)
- 2020-08-17 21:28:28下载
- 积分:1
-
matlab-CA
matlab的元胞自动机程序的源代码,胞自动机程序状态演化规则 ①如果一个元胞的状态是0,则当它有状态为1的邻元时,该元胞的状态以概率a×b变为1,并且当它的临域中状态为1的邻元越多,其状态转变为1的概率越大 ②如果一个元胞的状态是1,则该元胞的状态保持不变。初始传播者位于中心单元格25×25处
取50×50的网格,临域为Moore型,经过50个仿真时钟,知识传播结果的模拟图
(matlab Cellular Automata procedure source code, cellular automata evolution rules of procedure state ① If a cell' s state is 0, then when it has a status of one element of the neighborhood, the cellular state to the probability of a × b into one, and when it' s Pro domain status is one more element of the neighborhood, its status into a greater probability of 1 ② If a cell' s state is 1, the cellular status remains unchanged. Initial spreaders center cell 25 × 25 obtain 50 × 50 grid, the Pro domain for the Moore-type, after 50 simulation clock, the dissemination of knowledge of the simulation results of Figure)
- 2009-02-13 10:27:11下载
- 积分:1
-
toolbox_fast_marching
The method mainly consists in considering a reference normal ECG segment and input ECG (unknown behavior) segment.
Each segment of the input ECG T is compared to the reference segment using SEA.
The SEA method outputs a measure in the range [0..1] in terms of the correlation factor that reflects the degree of similarity between the reference and the segment under analysis. Based on this measure, the whole segment is classified as normal or abnormal.
A user specified threshold value on the correlation factor c is used for decision
- 2011-11-10 13:11:39下载
- 积分:1