Abstract：In order to analyze the change law and tendency of height data of IGS continuous operation reference station and predict the future changes of the height data over a period of time, based on the theories of RBF regularization neural network and wavelet filter neural networks, the height component data of Beijing IGS station is dealt with the GRNN function approximation and wavelet decomposition approximation on the basis of the MATLAB7.0 platform. According to the fitting historical height data and hierarchical filtering, the seasonal changes were found in height time series, and seasonal changes included half year cycle changes and year cycle changes, and the year cycle was obvious.
Zhao Gang,Zhang Sihui,Zhang Hengjing et al. ANALYSIS ON HEIGHT TIME SERIES OF IGS BASED ON RBF AND
FILTERING NEURAL NETWORK[J]. jgg, 2013, 33(5): 136-139.
