Title :
Maximum entropy property of discrete-time stable spline kernel
Author :
Ardeshiri, Tohid ; Tianshi Chen
Author_Institution :
Dept. of Electr. Eng., Linkoping Univ., Linkoping, Sweden
Abstract :
In this paper, the maximum entropy property of the discrete-time first-order stable spline kernel is studied. The advantages of studying this property in discrete-time domain instead of continuous-time domain are outlined. One of such advantages is that the differential entropy rate is well-defined for discrete-time stochastic processes. By formulating the maximum entropy problem for discrete-time stochastic processes we provide a simple and self-contained proof to show what maximum entropy property the discrete-time first-order stable spline kernel has.
Keywords :
maximum entropy methods; stochastic processes; continuous-time domain; discrete-time domain; discrete-time first-order stable spline kernel; discrete-time stochastic processes; maximum entropy property; Entropy; Gaussian processes; Indexes; Kernel; Splines (mathematics); White noise; Gaussian process; Machine learning; impulse response estimation; maximum entropy (MaxEnt);
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on
Conference_Location :
South Brisbane, QLD
DOI :
10.1109/ICASSP.2015.7178657