It is proved by the perturbation analysis of Signal Subspace that the performances of the method presented here are better than the improved spatial smoothingtechniques.
信号子空间的扰动分析表明,这种方法优于修正的空间平滑方法。
2
The present smoothingtechniques have solved the data sparse problem effectively but have not further analyzed the reasonableness for the frequency distribution of events occurring.
The present smoothingtechniques deal with the data sparse problem using different discount and compensate strategy, and they have different merit or shortcoming on complexity and rationality.