Qing Li, Zhigang Deng, et al.
IEEE T-MI
Partially Hidden Markov Models (PHMM) are introduced. They differ from the ordinary HMM's in that both the transition probabilities of the hidden states and the output probabilities are conditioned on past observations. As an illustration they are applied to black and white image compression where the hidden variables may be interpreted as representing noncausal pixels. © 1996 IEEE.
Qing Li, Zhigang Deng, et al.
IEEE T-MI
Liqun Chen, Matthias Enzmann, et al.
FC 2005
Charles H. Bennett, Aram W. Harrow, et al.
IEEE Trans. Inf. Theory
Beomseok Nam, Henrique Andrade, et al.
ACM/IEEE SC 2006