Automatic taxonomy generation: Issues and possibilities
Raghu Krishnapuram, Krishna Kummamuru
IFSA 2003
The Q-Coder is an important new development in binary arithmetic coding. It combines a simple but efficient arithmetic approximation for the multiply operation, a new formalism which yields optimally efficient hardware and software implementations, and a new technique for estimating symbol probabilities which matches the performance of any method known. This paper describes the probability-estimation technique. The probability changes are estimated solely from renormalizations in the coding process and require no additional counters. The estimation process can be implemented as a finite-state machine, and is simple enough to allow precise theoretical modeling of single-context coding. Approximate models have been developed for a more complex multi-rate version of the estimator and for mixed-context coding. Experimental studies verifying the modeling and showing the performance achieved for a variety of image-coding models are presented.
Raghu Krishnapuram, Krishna Kummamuru
IFSA 2003
Xiaozhu Kang, Hui Zhang, et al.
ICWS 2008
Yigal Hoffner, Simon Field, et al.
EDOC 2004
Raymond F. Boyce, Donald D. Chamberlin, et al.
CACM