Wavelet thresholding techniques for power spectrum estimation

The logarithm of an unknown power spectrum S(f) of a stationary random process is represented by a nonparametric method based on wavelet representation. The estimation of S(f) of a stationary random process is a nonparametric statistical estimation problem. The statistically significant constituents of the logarithm of S(f) at different resolution levels are captured by this approach. The proposed wavelet thresholding technique helps solve the nonparametric statistical estimation problem.