Title :
Refined Kalman smoothing for decoding real convolutional codes
Author_Institution :
Dept. of Electr. & Comput. Eng., California Univ., Davis, CA, USA
Abstract :
Real number convolutional codes can be corrected by time-varying smoothed Kalman estimation. The smoothing process can be truncated whenever the tracking innovations fall below a precomputed matrix norm
Keywords :
Kalman filters; convolutional codes; decoding; error correction codes; recursive estimation; stochastic processes; tracking; decoding real convolutional codes; precomputed matrix norm; refined Kalman smoothing; time-varying smoothed Kalman estimation; tracking; Convolutional codes; Covariance matrix; Decoding; Equations; Error correction; Kalman filters; Recursive estimation; Smoothing methods; Stochastic processes; Technological innovation;
Conference_Titel :
Information Theory, 1998. Proceedings. 1998 IEEE International Symposium on
Conference_Location :
Cambridge, MA
Print_ISBN :
0-7803-5000-6
DOI :
10.1109/ISIT.1998.708844
