multiScale_KalmanFilter

  用多尺度卡尔曼滤波法，对信号参数进行识别估计。高频信号和低频信号识别结合起来改进了算法识别的精确度和准确度。(It is an implementation of hierarchical (a.k.a. multi-scale) Kalman filter using belief propagation. The model parameters are estimated by expectation maximization (EM) algorithm. In this implementation, we considered two time series with different frequencies. The messages between high and low frequency signals are combined to improve the estimation and prediction.)

license.txt,1332,2013-01-04
multiScale_KalmanFilter
.......................\abstractsubformat-BME2012.pdf,314100,2012-10-20
.......................\Demo_KalmanFilter_BP_multiScale.m,1828,2012-10-18
.......................\EMConvergence.m,1489,2012-09-08
.......................\EMForMultiScaleKalmanFilter.m,3859,2012-09-04
.......................\eyeInf.m,88,2012-08-15
.......................\GaussianDivision.m,593,2012-08-28
.......................\GaussianMultiply.m,591,2012-08-20
.......................\gaussian_prob.m,848,2012-09-04
.......................\getCurrentZID.m,207,2012-08-20
.......................\initializeMessage.m,8632,2012-08-28
.......................\inv_s.m,421,2012-08-20
.......................\kalmanFilter_MultiScale.m,3971,2012-08-29
.......................\kalmanSmoother_MultiScale.m,2633,2012-08-28
.......................\linspaceInt.m,909,2012-08-24
.......................\timeSeriesDataGeneration.m,6572,2012-09-04
.......................\updateMSGInLevel2.m,582,2012-08-29
.......................\updateMSGToLevel2Backward.m,1007,2012-08-29