Restoration of Noisy 1/f-Type Fractal Signal Based on Orthonormal Wavelet Transform
YU Sheng-lin · Nanjing Hangkong Hangtian Daxue xuebao · 2004
As one of the most typical models of 1/f-type fractal signal, fractal Brownian motion (FBM) has some unique characteristics. In order to filter noisy FBM, noisy DFGN is transformed based on the wavelet. The detailed coefficients and approximation coefficients are estimated by least variance rule, which are then used to reconstruct DFGN. Then FBM is estimated from the reconstructed DFGN. In the digital simulation, the mean square error ( mse ) of the restored FBM and root mean square error ( rms ) of estimated Hurst show the validity and the preponderance of the algorithm.