The controllability and stability of wavelet networks are analyzed and proved . to reduce the modeling error in the piecewise linearization of nonlinear system , a multiple models wavelet networks identification method is proposed 針對(duì)非線性系統(tǒng)建模中使用分段線性化方法所帶來(lái)的未建模誤差問(wèn)題,提出了多模型小波網(wǎng)絡(luò)系統(tǒng)辨識(shí)方法。
Kalman filter is an optimal filter algorithm in the minimum - mean - square - error sense , meanwhile extended kalman filter is a sub - optimal filter algorithm , which derived from the linearization of nonlinear system using taylor expansion . while the non - linearity of the system is not extreme strong , ekf can achieve approximately optimal filter effect Kf是最小均方意義下的最優(yōu)濾波算法, ekf則是利用一階泰勒展開(kāi)將非線性系統(tǒng)線性化而得到的一種次優(yōu)濾波算法,在非線性不是特別嚴(yán)重的情況下, ekf有著近似最優(yōu)的濾波效果。