登录
首页 » matlab » Kalmanprediction

Kalmanprediction

于 2006-08-28 发布 文件大小:1KB
0 203
下载积分: 1 下载次数: 64

代码说明:

  利用Kalman预测对信号进行预测,信号源为《现代数字信号处理导论》上册,P202,习题5。(use of signal forecast Signal Source "Modern digital signal processing" Introduction to the first volume, P202, Exercise 5.)

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • proje
    applied k means clustering for vector quanta and used huffman for image compression matlab code
    2010-06-06 21:18:48下载
    积分:1
  • MatlabGUIHarris
    Harris 角点检测算法,可用于提取一幅图像中的所有角点,对于图像识别有很重要的意义。(Harris corner detection algorithm, an image can be used to extract all the corners, the image recognition has important significance.)
    2011-05-13 19:47:22下载
    积分:1
  • WaveletEnergySpectrum
    Matlab小波能量谱的程序wavelet energy spectrum (wavelet energy spectrum )
    2020-06-29 17:20:02下载
    积分:1
  • liantongxing
    通过Monte Carlo模拟法计算IEEE 79系统失负荷量,要求放在F盘下运行(Computing IEEE 79 system via Monte Carlo simulation method loss of load, run under the requirements placed on the F drive)
    2014-11-11 16:54:53下载
    积分:1
  • Russian_SquareV2.0
    俄罗斯方块matlab GUI平台的例程,自带程序说明(Tetris routines matlab GUI platform, comes with the program description)
    2013-12-18 19:53:46下载
    积分:1
  • gammatonegram
    gammatonegram of wav file usinf gammatone filter
    2015-04-11 17:01:29下载
    积分:1
  • thecontrolofMATLABSimulink
    《过程控制工程及仿真基于MATLABSimulink》的ppt,非常好的资料(" Process control engineering and simulation-based MATLABSimulink" the ppt, very good information)
    2010-11-16 19:59:37下载
    积分:1
  • photo_everyday
    运行该程序会在路径【F:图片\美好心情】上生成一幅照片,其名字为当前的拍摄时间。 1、需事先建立路径【F:图片\美好心情】 2、电脑为windows系统且配有摄像头(Run this program in the path [F: Pictures a better mood] to generate a photo, their name for the current recording time. 1, prior to the establishment of the path [F: Pictures a better mood] 2, the computer system for windows and with camera)
    2012-04-05 10:18:19下载
    积分:1
  • source-code
    source code pso fractical
    2011-07-10 16:44:02下载
    积分:1
  • adaboost
    Adaboost是一种迭代算法,其核心思想是针对同一个训练集训练不同的分类器(弱分类器),然后把这些弱分类器集合起来,构成一个更强的最终分类器(强分类器)。 load clouds [test_targets, E] = lijsada_boost(patterns, targets, patterns, 100, Stumps ,[]) train_patterns 每列为一样本 train_targets 每列为一样本目标 100 :Number Of Iterations Stumps: Weak Learner Type Learner s parameters :[] adaboost +stumps testRightR = 0.7522(Adaboost is an iterative algorithm)
    2014-01-20 13:05:34下载
    积分:1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载