Math_CAI_PPT

由于传感器自身以及通信延迟等原因, 使得异步多传感器数据融合问题比同步问题的研究更 切合实际。 对连续时间系统在融合中心和各传感器节点分别进行异步离散化处理,离散后过程噪声与测 量噪声以及测量噪声之间相关,虽然相应连续时间系统中的噪声是不相关的。 最后推导了相关噪声情况 下的异步融合算法,仿真结果说明了算法的有效性。(Due to t he r easons of senso rs in it self and the communication delays, the r esearch of t he asy nchr onous multisensor da ta fusion pr oblem is mo re pr actical than t hat o f synchro no us one. Firstly t he continuo us-time system is discr etig ed in the fusio n center and all t he senso r nodes w it h differ ent sample interv al. T hen the measurement no ises are fo und to be co r related with each other and t he pr o- cess noise tho ugh the no ises of t he co rr espo nding continuo us-time sy st em ar e unco rr elat ed. Finally an asy nchr onous fusion algo r ithm is pr esented for the cor r elat ed noises case. Simulatio n results show t he v alidity o f the presented a lg or ithm)

说明：  单一变量遗传算法程序，不包含子程序 (Single variable genetic algorithm program does not contain the subroutine)

短时傅立叶变换与魏格纳威尔分部相结合的时频分析算法以及自适应短时傅立叶变换( U77ED u65F6 u5085 u7ACB u53F6 u53D8 u6362 u4E0E u9B4F u683C u7EB3 u5A01 u5C14 u5206 u90E8 u76F8 u7ED3 u5408 u7684 u65F6 u9891 u5206 u6790 u7B97 u6CD5 u4EE5 u53CA u81EA u9002 u5E94 u77ED u65F6 u5085 u7ACB u53F6 u53D8 u6362)

基于conturlet变换的图像融合,利用conturlet还变来对图形进行处理并融合(Transform based image fusion conturlet transform based image fusion conturlet transform based image fusion conturlet)

利用matlab实现的蒙特卡罗算法代码,大家可以一起究研一下!(Monte Carlo algorithm is implemented using matlab code, we can study with the study look at!)

A* PATH PLANNING 使用經典A*演算法所做的路徑規劃(A* PATH PLANNING)

不同长度的LT码在高斯信道中的仿真，里面有编码程序，译码程序。(Different lengths of LT codes in Gaussian channel simulation, coding procedures, the decoding process.)

高斯平滑的matlab程序。参数可以随意设置，经过调试，准确(Gaussian smoothing of the matlab program. Parameters can be arbitrarily set, after commissioning, accurate)

说明：  matlab使用的卡罗曼工具箱，经典源码(Kaluoman use of Matlab Toolbox, classic source)

这是基于matlab的信号系统实验程序，可以完成信号系统课程的相关实验，提高信号系统课程的认识和理解。(This is based on the signaling system matlab experimental procedure, you can complete courses related experiments signaling system, improve the signal system course knowledge and understanding.)