Unsupervised probabilistic segmentation of motion data for mimesis modeling
暂无分享,去创建一个
[1] Lawrence R. Rabiner,et al. A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.
[2] Jonathan J. Oliver,et al. Bayesian Approaches to Segmenting A Simple Time Series , 1997 .
[3] Jeff A. Bilmes,et al. A gentle tutorial of the em algorithm and its application to parameter estimation for Gaussian mixture and hidden Markov models , 1998 .
[4] Yoshihiko Nakamura,et al. Acquisition and embodiment of motion elements in closed mimesis loop , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).
[5] Jens Kohlmorgen. On optimal segmentation of sequential data , 2003, 2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718).
[6] Yoshihiko Nakamura,et al. From Stochastic Motion Generation and Recognition to Geometric Symbol Development and Manipulation , 2003 .
[7] Stefano Nolfi,et al. Learning to perceive the world as articulated: an approach for hierarchical learning in sensory-motor systems , 1998, Neural Networks.
[8] Klaus-Robert Müller,et al. Analysis of switching dynamics with competing neural networks , 1995 .
[9] Michael I. Jordan,et al. Hierarchical Mixtures of Experts and the EM Algorithm , 1994, Neural Computation.