Effective DDoS Attacks Detection Using Generalized Entropy Metric
ICA3PP '09 Proceedings of the 9th International Conference on Algorithms and Architectures for Parallel Processing
IEEE Transactions on Image Processing
Characterization of second-order isotropic fractional brownian fields
IEEE Transactions on Signal Processing
Two-channel nonseparable wavelets statistically matched to 2-D images
Signal Processing
Fractal and EMD based removal of baseline wander and powerline interference from ECG signals
Computers in Biology and Medicine
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A generalization of fractional Brownian motion (fBm) of parameter H in ]0, 1[ is proposed. More precisely, this work leads to nth-order fBm (n-fBm) of H parameter in ]n-1, n[, where n is any strictly positive integer. They include fBm for the special case n=1. Properties of these new processes are investigated. Their covariance function are given, and it is shown that they are self similar. In addition, their spectral shape is assessed as 1/fα with α belonging to ]1; +∞[, providing a larger framework than classical fBm. Special interest is given to their nth-order stationary increments, which extend fractional Gaussian noises. The covariance function and power spectral densities are calculated. The properties and signal processing tasks such as a Cholesky-type synthesis technique and a maximum likelihood estimation method of the H parameter are presented. The results show that the estimator is efficient (unbiased and reaches the Cramer-Rao lower bound) for a large majority of tested values