Efficient seismic sparse decomposition based on multiple kernel-based models

To enhance the efficiency and sparsity of seismic signal decomposition, multiple kernels are used for the adaptive sparse decomposition of seismic signals. At first, the global k-means clustering algorithm is utilized to generate the preselected behavioral parameters in the dictionary. Then the signal is reconstructed with orthogonal least squares method. The experiments both on synthetic and real data were conducted to evaluate the performance. The results show that multiple kernel-based models greatly improve the sparsity with the similar accuracy. ©, 2015, Science Press. All right reserved.