【摘要】 对复Gauss-ian小波满足M ercy条件及其在H ilbert空间具有再生性的命题作了证明.用复Gauss-ian小波构建出一种核函数,与主成分分析方法相结合,对非线性非平稳信号进行参数辨识和预测.针对多参数模型优化时间过长,不利于工程应用的问题,提出了一种多参数同步优化策略.仿真实验验证了该方法的可行性和有效性,表明该方法具有较好的实用价值.yh更多还原

【Abstract】 This paper proves the proposition that complex Gaussian wavelet can satisfy the Mercy conditions and exhibits reproduction features in Hilbert space.A special kernel function named complex Gaussian wavelet kernel function is built,which is combined with principal component analysis(PCA), to identify parameters and forecast future information of the non-linear dynamic signals.A multi-parameter synchronous optimization method is proposed to shorten the optimizatoin time in multi-parameter models.Simulation experiment results validate the feasibility and(effectiveness) of the method.更多还原