Stable behavior in a recurrent neural network for a finite state machine
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[1] Ryohei Nakano,et al. Adaptive β Scheduling Learning Method of Finite State Automata by Recurrent Neural Networks , 1997, ICONIP.
[2] Ryohei Nakano,et al. Annealed RNN Learning of Finite State Automata , 1996, ICANN.
[3] Mikel L. Forcada,et al. Stable Encoding of Finite-State Machines in Discrete-Time Recurrent Neural Nets with Sigmoid Units , 2000, Neural Computation.
[4] Raymond L. Watrous,et al. Induction of Finite-State Languages Using Second-Order Recurrent Networks , 1992, Neural Computation.
[5] A. M. Walker. On the Asymptotic Behaviour of Posterior Distributions , 1969 .
[6] C. Lee Giles,et al. Stable Encoding of Large Finite-State Automata in Recurrent Neural Networks with Sigmoid Discriminants , 1996, Neural Computation.
[7] Panagiotis Manolios,et al. First-Order Recurrent Neural Networks and Deterministic Finite State Automata , 1994, Neural Computation.
[8] Anders Krogh,et al. Introduction to the theory of neural computation , 1994, The advanced book program.
[9] David J. C. MacKay,et al. Bayesian Interpolation , 1992, Neural Computation.
[10] Ronald J. Williams,et al. A Learning Algorithm for Continually Running Fully Recurrent Neural Networks , 1989, Neural Computation.
[11] Marvin Minsky,et al. Computation : finite and infinite machines , 2016 .
[12] Jordan B. Pollack,et al. The induction of dynamical recognizers , 1991, Machine Learning.
[13] Geoffrey E. Hinton. Learning Translation Invariant Recognition in Massively Parallel Networks , 1987, PARLE.
[14] Mike Casey,et al. The Dynamics of Discrete-Time Computation, with Application to Recurrent Neural Networks and Finite State Machine Extraction , 1996, Neural Computation.
[15] Alberto Sanfeliu,et al. An Algebraic Framework to Represent Finite State Machines in Single-Layer Recurrent Neural Networks , 1995, Neural Computation.
[16] Mikel L. Forcada,et al. Learning the Initial State of a Second-Order Recurrent Neural Network during Regular-Language Inference , 1995, Neural Computation.
[17] Jeffrey L. Elman,et al. Finding Structure in Time , 1990, Cogn. Sci..
[18] Christopher M. Bishop,et al. Neural networks for pattern recognition , 1995 .
[19] Peter Tiño,et al. Learning and Extracting Initial Mealy Automata with a Modular Neural Network Model , 1995, Neural Comput..
[20] Padhraic Smyth,et al. Learning Finite State Machines With Self-Clustering Recurrent Networks , 1993, Neural Computation.
[21] Yoshua Bengio,et al. Learning long-term dependencies with gradient descent is difficult , 1994, IEEE Trans. Neural Networks.
[22] Srimat T. Chakradhar,et al. First-order versus second-order single-layer recurrent neural networks , 1994, IEEE Trans. Neural Networks.
[23] C. Lee Giles,et al. Constructing deterministic finite-state automata in recurrent neural networks , 1996, JACM.
[24] Jordan B. Pollack,et al. Analysis of Dynamical Recognizers , 1997, Neural Computation.
[25] Michael C. Mozer,et al. A Unified Gradient-Descent/Clustering Architecture for Finite State Machine Induction , 1993, NIPS.
[26] Philip E. Gill,et al. Practical optimization , 1981 .
[27] James L. McClelland,et al. Finite State Automata and Simple Recurrent Networks , 1989, Neural Computation.
[28] Michael C. Mozer,et al. Dynamic On-line Clustering and State Extraction: An Approach to Symbolic Learning , 1998, Neural Networks.
[29] C. Lee Giles,et al. Learning and Extracting Finite State Automata with Second-Order Recurrent Neural Networks , 1992, Neural Computation.