Wavelet transform based nonlınear predıctıon of sıgnals

Scientific Bulletin of the ''Petru Maior" University of Tîrgu Mureș

Horatiu-Stefan Grif¹  Zoltan German-Sallo¹ 

[1] "Petru Maior" University of Tîrgu Mureş Nicolae Iorga Street, no.1, Tîrgu Mureş, Romania;

关键词: prediction;    discrete wavelet transform;    artificial neural networks;    nonlinear approximation;    prediction error;   

DOI  :  

来源: DOAJ

【 摘 要 】

Estimating signals from time series is a common task in many domains of science and has been addressed for a long time by specialists. Predicting a signal from recorded time series remains however a very specific task, a great challenge. The wavelet transform provides multi-resolution analysis and allows accurate time-frequency localization of different signal properties. This paper presents a nonlinear prediction method implemented on artificial neural network based learning structure. From a discrete wavelet transform provided tree structure, specific coefficients are obtained and predicted with the already mentioned method, the reconstruction of signal is carried out using these new coefficients. The predicted signal is compared with the original one through parameters as the absolute mean error, using different analyzing functions and different learning structures. To evaluate the prediction, noise of different levels is added and the absolute mean error is recomputed and compared after every prediction.

【 授权许可】

Unknown