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Paper [L. Xu, Temporal BYY learning for state space approach, hidden Markov model and blind source separation, IEEE Trans. Signal Process. 48 (7) (2000) 2132–2144] has presented a temporal factor analysis (TFA) algorithm in state-space model through minimizing an approximate Kullback-divergence cost function. In this paper, we further study the TFA within the maximum-likelihood (ML) framework. Without...
A temporal extension of the classical factor analysis (FA) (Proceedings of the Berkeley Symposium on Mathematical Statistics and Probability, May 3, Berkeley, University of California, 1956, pp. 111-150.) has been made under the framework of temporal Bayesian Ying-Yang system (Proceedings of the International Conference on Neural Information Processing (ICONIP'98), Vol. 2, 1998, pp. 877-884; IEEE...
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