Hidden Markov models and neural networks for fault detection in dynamic systems
暂无分享,去创建一个
[1] P. Smyth,et al. Failure monitoring in dynamic systems: Model construction without fault training data , 1993 .
[2] Paul M. Frank,et al. Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy: A survey and some new results , 1990, Autom..
[3] Padhraic Smyth. Probability density estimation and local basis function neural networks , 1994, COLT 1994.
[4] Lawrence R. Rabiner,et al. A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.
[5] Padhraic Smyth,et al. On loss functions which minimize to conditional expected values and posterior proba- bilities , 1993, IEEE Trans. Inf. Theory.
[6] Andreas Stolcke,et al. Hidden Markov Model} Induction by Bayesian Model Merging , 1992, NIPS.
[7] E. Ayanoglu. Robust and fast failure detection and prediction for fault-tolerant communication network , 1992 .
[8] J. Berger. Statistical Decision Theory and Bayesian Analysis , 1988 .
[9] Padhraic J. Smyth,et al. Hidden Markov models for fault detection in dynamic systems , 1993 .
[10] Richard Lippmann,et al. Neural Network Classifiers Estimate Bayesian a posteriori Probabilities , 1991, Neural Computation.
[11] Alan S. Willsky,et al. A survey of design methods for failure detection in dynamic systems , 1976, Autom..
[12] Rolf Isermann,et al. Process fault detection based on modeling and estimation methods - A survey , 1984, Autom..