-
DSSS
this file gives an overall concept for dsss
- 2010-12-06 16:57:03下载
- 积分:1
-
Maximize-the-minimum-user
多主用户网络CR中动态频谱接入策略,使最小用户接入策略最大化。(Multi-user network CR main dynamic spectrum access strategy to maximize the minimum user access policies.)
- 2013-12-06 22:36:42下载
- 积分:1
-
jbfmxexn
Relief计算分类权重,阵列信号处理的高分辨率估计,FMCW调频连续波雷达的测距测角,多姿态,多角度,有不同光照,一些自适应信号处理的算法,pwm整流器的建模仿真。( Relief computing classification weight, High-resolution array signal processing estimates, FMCW frequency modulated continuous wave radar range and angular measurements, Much posture, multi-angle, have different light, Some adaptive signal processing algorithms, Modeling and simulation pwm rectifie.)
- 2016-03-12 11:30:05下载
- 积分:1
-
selectivecombining
diversity combining(SC.MRC.EGC.DC)(diversity combining)
- 2010-01-19 13:34:15下载
- 积分:1
-
Walsh
本方法是对二维医学图像实现的Walsh变换,属于预处理范围,为下一步的图像分割,配准等打下基础(This method is the realization of two-dimensional medical images of the Walsh transform, belong to the scope of pre-treatment, for the next phase of image segmentation, registration, etc. to lay the groundwork)
- 2008-01-22 10:40:00下载
- 积分:1
-
mitmatlab
说明: 数据挖掘中经典算法的matlab代码,相当全面!(Classical data mining algorithm matlab code, quite comprehensive!)
- 2008-09-22 14:46:24下载
- 积分:1
-
tikhonov
整理的tikhonov算法。包含一般的以及迭代的。有详细算例。(Tikhonov algorithm finishing. Contains general and iteration. Detailed studies.)
- 2021-05-16 19:30:08下载
- 积分:1
-
Sim
电机控制系统,02年开始积累,效果好,速度快,PI控制,经典控制,fuzzy PID,自适应控制,速度位置控制等等,欢迎大家参考。(Servo motor control system, in 2002 began to accumulate, effective, fast, PI control, classical control, fuzzy PID, adaptive control, speed position control, etc., we welcome the reference.)
- 2013-12-11 14:18:26下载
- 积分:1
-
code
说明: 非线性分类,SVM理论为基础,调整参数改变分类(聚类的)边界的松紧程度(Nonlinear classification, SVM theory, adjust the parameters to change the classification (clustering) the degree of elastic boundary)
- 2008-09-19 18:07:59下载
- 积分:1
-
Multi-objective-genetic-algorithm
Real world problems often present multiple, frequently conflicting, objectives.
The research for optimal solutions of multi-objective problems
can be achieved through means of genetic algorithms, which are inspired
by the natural process of evolution: an initial population of solutions is
randomly generated, then pairs of solutions are selected and combined in
order to create new solutions slightly different the initial solutions.
The fittest solutions are kept in the population and are used to generate
new solutions
- 2015-02-10 21:55:32下载
- 积分:1