Stable Encoding of Finite-State Machines in Discrete-Time Recurrent Neural Nets with Sigmoid Units
暂无分享,去创建一个
Mikel L. Forcada | Rafael C. Carrasco | Ramón P. Ñeco | M. Ángeles Valdés-Muñoz | M. Forcada | R. Ñeco | M. Á. Valdés-Muñoz
[1] Ah Chung Tsoi,et al. Discrete time recurrent neural network architectures: A unifying review , 1997, Neurocomputing.
[2] Kazutoshi Gohara,et al. Fractal Transition in continuous Recurrent Neural Networks , 2001, Int. J. Bifurc. Chaos.
[3] Mikel L. Forcada,et al. Constrained Second-Order Recurrent Networks for Finite-State Automata Induction , 1998 .
[4] Mikel L. Forcada,et al. Simple Strategies to Encode Tree Automata in Sigmoid Recursive Neural Networks , 2001, IEEE Trans. Knowl. Data Eng..
[5] Eduardo D. Sontag,et al. Analog Neural Nets with Gaussian or Other Common Noise Distributions Cannot Recognize Arbitrary Regular Languages , 1999, Neural Computation.
[6] Stefan C. Kremer,et al. On the computational power of Elman-style recurrent networks , 1995, IEEE Trans. Neural Networks.
[7] J. R,et al. Analog Stable Simulation of Discrete Neural Networks , 1997 .
[8] Alberto Sanfeliu,et al. An Algebraic Framework to Represent Finite State Machines in Single-Layer Recurrent Neural Networks , 1995, Neural Computation.
[9] Marvin Minsky,et al. Computation : finite and infinite machines , 2016 .
[10] Rafael C. Carrasco,et al. Efficient encoding of finite automata in discrete-time recurrent neural networks , 1999 .
[11] S. Hyakin,et al. Neural Networks: A Comprehensive Foundation , 1994 .
[12] Mikel L. Forcada,et al. Inferring stochastic regular grammars with recurrent neural networks , 1996, ICGI.
[13] Peter Tiňo,et al. Finite State Machines and Recurrent Neural Networks -- Automata and Dynamical Systems Approaches , 1995 .
[14] D.R. Hush,et al. Progress in supervised neural networks , 1993, IEEE Signal Processing Magazine.
[15] C. Lee Giles,et al. Experimental Comparison of the Effect of Order in Recurrent Neural Networks , 1993, Int. J. Pattern Recognit. Artif. Intell..
[16] M. Goudreau,et al. First-order vs. Second-order Single Layer Recurrent Neural Networks , 1994 .
[17] C. Lee Giles,et al. Constructing deterministic finite-state automata in recurrent neural networks , 1996, JACM.
[18] W S McCulloch,et al. A logical calculus of the ideas immanent in nervous activity , 1990, The Philosophy of Artificial Intelligence.
[19] John F. Kolen,et al. The observers' paradox: apparent computational complexity in physical systems , 1995, J. Exp. Theor. Artif. Intell..
[20] Mikel L. Forcada,et al. Encoding of sequential translators in discrete-time recurrent neural nets , 1999, ESANN.
[21] Frank Fallside,et al. A recurrent error propagation network speech recognition system , 1991 .
[22] Jeffrey L. Elman,et al. Finding Structure in Time , 1990, Cogn. Sci..
[23] Ryohei Nakano,et al. Adaptive β Scheduling Learning Method of Finite State Automata by Recurrent Neural Networks , 1997, ICONIP.
[24] Renée Elio,et al. A theory of grammatical induction in the connectionist paradigm , 1996 .
[25] Padhraic Smyth,et al. Learning Finite State Machines With Self-Clustering Recurrent Networks , 1993, Neural Computation.
[26] Marco Gori,et al. Recurrent neural networks can learn simple, approximate regular languages , 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).
[27] Andrew S. Noetzel,et al. Forcing Simple Recurrent Neural Networks to Encode Context , 1992 .
[28] Panagiotis Manolios,et al. First-Order Recurrent Neural Networks and Deterministic Finite State Automata , 1994, Neural Computation.
[29] Ryohei Nakano,et al. Annealed RNN Learning of Finite State Automata , 1996, ICANN.
[30] James L. McClelland,et al. Finite State Automata and Simple Recurrent Networks , 1989, Neural Computation.
[31] John F. Kolen,et al. Fool's Gold: Extracting Finite State Machines from Recurrent Network Dynamics , 1993, NIPS.
[32] Jeffrey D. Ullman,et al. Introduction to Automata Theory, Languages and Computation , 1979 .
[33] Srimat T. Chakradhar,et al. First-order versus second-order single-layer recurrent neural networks , 1994, IEEE Trans. Neural Networks.
[34] Jordan B. Pollack,et al. Analysis of Dynamical Recognizers , 1997, Neural Computation.
[35] Thomas L. Floyd. Digital Fundamentals , 1986 .
[36] Efficient encodings of finite automata in discrete-time recurrent neural networks ∗ , 1999 .
[37] Noga Alon,et al. Efficient simulation of finite automata by neural nets , 1991, JACM.
[38] Michael C. Mozer,et al. Dynamic On-line Clustering and State Extraction: An Approach to Symbolic Learning , 1998, Neural Networks.
[39] Peter Tiño,et al. Learning and Extracting Initial Mealy Automata with a Modular Neural Network Model , 1995, Neural Comput..
[40] C. Lee Giles,et al. An experimental comparison of recurrent neural networks , 1994, NIPS.
[41] Giovanni Soda,et al. Inductive inference from noisy examples using the hybrid finite state filter , 1998, IEEE Trans. Neural Networks.
[42] Jirí Wiedermann,et al. Theory of neuromata , 1998, JACM.
[43] Yoshua Bengio,et al. Learning long-term dependencies with gradient descent is difficult , 1994, IEEE Trans. Neural Networks.
[44] Piotr Indyk. Optimal Simulation of Automata by Neural Nets , 1995, STACS.
[45] Anders Krogh,et al. Introduction to the theory of neural computation , 1994, The advanced book program.
[46] Don R. Hush,et al. Bounds on the complexity of recurrent neural network implementations of finite state machines , 1993, Neural Networks.
[47] Mike Casey,et al. The Dynamics of Discrete-Time Computation, with Application to Recurrent Neural Networks and Finite State Machine Extraction , 1996, Neural Computation.
[48] Pekka Orponen,et al. On the Effect of Analog Noise in Discrete-Time Analog Computations , 1996, Neural Computation.
[49] C. Lee Giles,et al. Stable Encoding of Large Finite-State Automata in Recurrent Neural Networks with Sigmoid Discriminants , 1996, Neural Computation.
[50] Mikel L. Forcada,et al. Learning the Initial State of a Second-Order Recurrent Neural Network during Regular-Language Inference , 1995, Neural Computation.
[51] Raymond L. Watrous,et al. Induction of Finite-State Languages Using Second-Order Recurrent Networks , 1992, Neural Computation.
[52] Michael Casey. Correction to Proof That Recurrent Neural Networks Can Robustly Recognize Only Regular Languages , 1998, Neural Computation.
[53] Alberto Sanfeliu,et al. Active Grammatical Inference: A New Learning Methodology , 1994 .
[54] C. Lee Giles,et al. Learning and Extracting Finite State Automata with Second-Order Recurrent Neural Networks , 1992, Neural Computation.
[55] Padhraic Smyth,et al. Discrete recurrent neural networks for grammatical inference , 1994, IEEE Trans. Neural Networks.
[56] Ryohei Nakano,et al. Stable behavior in a recurrent neural network for a finite state machine , 2000, Neural Networks.
[57] L. K. Li,et al. Fixed point analysis for discrete-time recurrent neural networks , 1992, [Proceedings 1992] IJCNN International Joint Conference on Neural Networks.
[58] S C Kleene,et al. Representation of Events in Nerve Nets and Finite Automata , 1951 .