Identification of a specific limitation on local-feedback recurrent networks acting as Mealy-Moore machines
Describes a proof which identifies limitations of local-feedback recurrent networks (LFRNs) in representing Mealy-Moore machines. Specifically, the paper identifies a class of machines that are unrepresentable in these networks. While it is known that LFRNs cannot represent all automata, this is the...
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| Published in | IEEE transactions on neural networks Vol. 10; no. 2; pp. 433 - 438 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
New York, NY
IEEE
1999
Institute of Electrical and Electronics Engineers |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1045-9227 |
| DOI | 10.1109/72.750574 |
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| Abstract | Describes a proof which identifies limitations of local-feedback recurrent networks (LFRNs) in representing Mealy-Moore machines. Specifically, the paper identifies a class of machines that are unrepresentable in these networks. While it is known that LFRNs cannot represent all automata, this is the first paper to show a specific class of unrepresentable automata. The paper goes beyond previous work in the area by addressing realistic activation functions, arbitrary network architectures, and more general computing machines. |
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| AbstractList | This paper describes a proof which identifies limitations of local-feedback recurrent networks (LFRN's) in representing Mealy-Moore machines. Specifically, it identifies a class of machines that are unrepresentable in these networks. While it is known that LFRN's cannot represent all automata, this is the first paper to show a specific class of unrepresentable automata. The paper goes beyond previous work in the area by addressing realistic activation functions, arbitrary network architectures, and more general computing machines. Describes a proof which identifies limitations of local-feedback recurrent networks (LFRNs) in representing Mealy-Moore machines. Specifically, the paper identifies a class of machines that are unrepresentable in these networks. While it is known that LFRNs cannot represent all automata, this is the first paper to show a specific class of unrepresentable automata. The paper goes beyond previous work in the area by addressing realistic activation functions, arbitrary network architectures, and more general computing machines. This paper describes a proof which identifies limitations of local-feedback recurrent networks (LFRN's) in representing Mealy-Moore machines. Specifically, it identifies a class of machines that are unrepresentable in these networks. While it is known that LFRN's cannot represent all automata, this is the first paper to show a specific class of unrepresentable automata. The paper goes beyond previous work in the area by addressing realistic activation functions, arbitrary network architectures, and more general computing machines.This paper describes a proof which identifies limitations of local-feedback recurrent networks (LFRN's) in representing Mealy-Moore machines. Specifically, it identifies a class of machines that are unrepresentable in these networks. While it is known that LFRN's cannot represent all automata, this is the first paper to show a specific class of unrepresentable automata. The paper goes beyond previous work in the area by addressing realistic activation functions, arbitrary network architectures, and more general computing machines. Describes a proof which identifies limitations of local-feedback recurrent networks (LFRNs) in representing Mealy-Moore machines. Specifically, the paper identifies a class of machines that are unrepresentable in these networks. While it is known that LFRNs cannot represent all automata, this is the first paper to show a specific class of unrepresentable automata. The paper goes beyond previous work in the area by addressing realistic activation functions, arbitrary network architectures, and more general computing machines |
| Author | Kremer, S.C. |
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| Cites_doi | 10.1162/neco.1992.4.1.120 10.1109/72.548181 10.1109/72.508949 10.1080/09540099208946601 10.1145/130385.130432 10.1002/j.1538-7305.1955.tb03788.x 10.1145/103516.103523 10.1515/9781400882618-006 10.1109/72.286928 10.1109/72.536316 10.1109/69.382304 10.1109/72.392262 10.1109/72.392247 10.1109/72.279187 |
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| Keywords | Finite state machine Network architecture Identification Mealy-Moore machine Neural network Dynamical system Learning algorithm Computing machine Recurrent neuronal network |
| Language | English |
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| References | ref13 kremer (ref15) 1996 ref14 ref11 hopcroft (ref12) 1979 fahlman (ref9) 1991 ref2 ref1 ref17 ref16 ref18 ref8 ref7 ref4 horne (ref10) 1995 ref6 ref5 moore (ref3) 1956 |
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| Snippet | Describes a proof which identifies limitations of local-feedback recurrent networks (LFRNs) in representing Mealy-Moore machines. Specifically, the paper... This paper describes a proof which identifies limitations of local-feedback recurrent networks (LFRN's) in representing Mealy-Moore machines. Specifically, it... |
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| SubjectTerms | Activation Applied sciences Architecture Automata Automation Computation Computer architecture Computer networks Councils Electric, optical and optoelectronic circuits Electronics Exact sciences and technology Gradient methods Information science Logistics Mathematical analysis Mathematical models Networks Neural networks Neurofeedback Robustness State feedback |
| Title | Identification of a specific limitation on local-feedback recurrent networks acting as Mealy-Moore machines |
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