Title :
Sinusoidal signal detection using the minimum description length and the predictive stochastic complexity
Author :
Valaee, S. ; Champagne, B. ; Kabal, P.
Author_Institution :
Dept. of Electr. Eng., Tarbiat Modares Univ., Tehran, Iran
Abstract :
Two techniques based on the minimum description length (MDL) and the predictive stochastic complexity (PSC) are proposed for sinusoidal signal detection. The MDL and PSC criteria are the codelength of the observation and the model. The proposed techniques decompose the observation vector into its components in the signal and noise subspaces. The noise component is encoded for several model orders. The best model is selected by minimizing the codelength
Keywords :
encoding; prediction theory; signal detection; stochastic processes; time series; codelength; encoding; minimum description length; model orders; noise component; observation vector; predictive stochastic complexity; sinusoidal signal detection; Frequency; Probability density function; Signal detection; Signal generators; Stochastic processes; Tiles; White noise;
Conference_Titel :
Digital Signal Processing Proceedings, 1997. DSP 97., 1997 13th International Conference on
Conference_Location :
Santorini
Print_ISBN :
0-7803-4137-6
DOI :
10.1109/ICDSP.1997.628538
