## Prepared By: (2002)

### BibTeX

@MISC{Harold02preparedby:,

author = {Mr. Harold and D. Coleman and Grants Officer and Mr. Nelson and H. Keeler and Nasa Iv and Ken Mcgill and Christina Moats and Brian J. Taylor and Marjorie Darrah},

title = {Prepared By:},

year = {2002}

}

### OpenURL

### Abstract

This Report includes data that shall not be disclosed outside the Government and shall not be duplicated, used, or disclosed in whole or in part for any purpose other than to evaluate this Report. This restriction does not limit the right of the Government to use information contained in this Report if it is proprietary data contained herein, if obtained from another source without restriction. The data subject to this restriction are contained in all sheets of this Report. The proprietary data contained herein, if disclosed to the public, would affect ISR’s competitive position in obtaining business; therefore, it is considered to be exempt from public release under the Freedom of Information Act (5 USC §552, as amended), paragraph (b)(4). IVVNN-LITREV-F002-UNCLASS-111202

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(Show Context)
Citation Context ... known as the Boltzmann machine, which was the first successful realization of a multilayer NN. This work with the Boltzmann machine provided the foundation for the linking of NNs to belief networks [=-=Pearl 1988-=-] and, in particular, for the development of sigmoid belief networks by Neal [Neal 1992]. In 1986, D.E. Rumelhart and J.L.McClellan, in their monumental two-volume work Parallel Distributed Processing... |

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1578 |
Neural networks and physical systems with emergent collective computational abilities
- Hopfield
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Citation Context ...n 1982]. In 1982, J.J. Hopfield introduced the use of an energy function in formulating a new way of understanding the computation performed by recurrent networks with symmetric synaptic connections [=-=Hopfield 1982-=-]. This new perspective, based on energy principles, resulted in attracted many researchers from other scientific disciplines, such as physics, to explore and contribute to the field of NNs. The Hopfi... |

1501 | The Temporal Logic of Reactive and Concurrent Systems: Specifications. The Temporal Logic of Reactive and Concurrent Systems - Manna, Pnueli - 1992 |

1093 |
Self-organized formation of topologically correct feature maps
- Kohonen
- 1982
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Citation Context ...es a bottom-up recognition layer and a topdown generative layer [Grossburg 1980]. Later, in 1982, Tuevo Kohonen introduced the development of SOMs based on one- or two-dimensional lattice structures [=-=Kohonen 1982-=-]. In 1982, J.J. Hopfield introduced the use of an energy function in formulating a new way of understanding the computation performed by recurrent networks with symmetric synaptic connections [Hopfie... |

716 | A logical calculus of the ideas immanent in nervous activity - McCulloch, Pitts - 1943 |

470 | Symbolic model checking for real-time systems - Henzinger, Nicollin, et al. - 1994 |

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Citation Context ...4, Minsky developed his thesis on “Theory of Neural-Analog Reinforcement Systems and Its Application to the BrainModel Problem” [Minsky 1954]. Minsky’s book Computation: Finite and Infinite Machines [=-=Minsky 1967-=-] extended the 1943 results of McCulloch and Pitts by explaining them in the context of automata theory and the theory of computation. Use or disclosure of data contained on this sheet is subject to t... |

434 | Multivariable functional interpolation and adaptive networks - Broomhead, Lowe - 1988 |

431 | A learning algorithm for Boltzmann machines - Ackley, Hinton, et al. - 1985 |

384 | Neural network ensembles, cross validation, and active learning - Krogh, Vedelsby - 1995 |

356 | HyTech: A Model Checker for Hybrid Systems - Henzinger, Ho, et al. - 1997 |

272 | Parallel Distributed Processing - Rumelhart, McClelland - 1986 |

266 | Automatic symbolic verification of embedded systems - Alur, Henzinger, et al. - 1996 |

238 | Distributed representations - Hinton, McClelland, et al. - 1986 |

234 | A survey and critique of techniques for extracting rules from trained artificial neural networks - Andrews, Diederich, et al. - 1995 |

213 |
Weak Second-order Arithmetic and Finite Automata
- Büchi
- 1960
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Citation Context ... an infinite family of networks by a single WS1S (Weak Second-order theory of 1 successor) transition system whose variables are set (2nd-order) variables and whose transitions are described in WS1S [=-=Buchi 1960-=-]. Second, PAX presents methods that allow one to abstract a WS1S system into a finite state system that can be model-checked. Third, to verify liveliness Use or disclosure of data contained on this s... |

196 | Extracting refined rules from knowledge-based neural networks - Towell, Shavlik - 1993 |

181 |
Connectionist learning of belief networks
- Neal
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(Show Context)
Citation Context ...yer NN. This work with the Boltzmann machine provided the foundation for the linking of NNs to belief networks [Pearl 1988] and, in particular, for the development of sigmoid belief networks by Neal [=-=Neal 1992-=-]. In 1986, D.E. Rumelhart and J.L.McClellan, in their monumental two-volume work Parallel Distributed Processing: Explorations in the Microstructure of Cognition [Rumelhart 1986], introduced the back... |

158 | Elementary Differential Equations and Boundary Value Problems - Boyce, DiPrima - 1991 |

143 | A user guide to HyTech - Henzinger, Ho, et al. - 1995 |

126 | Monitoring Java Programs with Java PathExplorer - Havelund, Rosu - 2001 |

100 | Java PathFinder - second generation of a Java model checker - Visser, Havelund, et al. - 2000 |

94 | The generalized railroad crossing — a case study in formal verification of real-time systems - Heitmeyer, Lynch - 1994 |

76 | Compiling real-time specifications into extended automata - Nicollin, Sifakis, et al. - 1992 |

73 | Using Sampling and Queries to Extract Rules from Trained Neural Networks - Craven, Shavlik - 1994 |

72 | Formal analysis of a space-craft controller using spin - Havelund, Lowry, et al. - 2001 |

67 | How patterned neural connections can be set up by self–organization - Willshaw, Malsburg - 1976 |

64 | Rule Generation from Neural Networks - Fu - 1994 |

63 | Tool-supported program abstraction for finite-state verification - Dwyer, Hatcliff, et al. - 2001 |

58 | Two examples of verification of multirate timed automata with Kronos - Daws, Yovine - 1995 |

58 | Centrality in Networks - Freeman - 1979 |

56 | Generalized verification diagrams - Browne, Manna, et al. - 1995 |

51 | STeP: Deductive-algorithmic verification of reactive and real-time systems - Bjørner, Browne, et al. |

49 | A new methodology of extraction, optimization and application of crisp and fuzzy logical rules - Duch, Adamczak, et al. - 2001 |

47 | Symbolic knowledge extraction from trained neural networks: A sound approach - Garcez, Broda, et al. |

46 | Direct transfer of learned information among neural networks - Pratt, Mostow, et al. - 1991 |

45 | Automated analysis of an audio control protocol - Ho, Wong-Toi - 1995 |

42 | The bounded retransmission protocol must be on time - D’Argenio, Katoen, et al. - 1997 |

42 | J.Misra: Parallel program design: a foundation - Chandy - 1988 |

41 | Learning symbolic rules using artificial neural networks - Craven, Shavlik - 1993 |

39 | Refinement of approximately correct domain theories by knowledge-based neural networks - Shavlik, Noordewier, et al. - 1990 |

38 |
The organization of behavior: A neurophysiological theory
- Hebb
- 1961
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Citation Context ... University in Canada, published a novel postulate of neural learning: the effectiveness of a synapse to transfer a signal between two neurons is increased by repeated activation across that synapse [=-=Hebb 1949-=-]. This theory, also known as “Hebb’s Rule,” explained the physiological concept of synaptic modification, the increase or decrease of a neuron’s response to electrical stimulus. This corresponds to t... |

37 | Formal verification of diagnosability via symbolic model checking - Cimatti, Pecheur, et al. - 2003 |

36 | Addressing Dynamic Issues of Program Model Checking. Model Checking Software - Lerda, Visser - 2001 |

32 | Formal analysis of the remote agent before and after flight - Havelund, Lowry, et al. - 2000 |

32 |
Theory of neural-analog reinforcement systems and its application to the brain-model problem
- Minsky
- 1954
(Show Context)
Citation Context ...al Intelligence Laboratory in 1959. While a student at Princeton in 1954, Minsky developed his thesis on “Theory of Neural-Analog Reinforcement Systems and Its Application to the BrainModel Problem” [=-=Minsky 1954-=-]. Minsky’s book Computation: Finite and Infinite Machines [Minsky 1967] extended the 1943 results of McCulloch and Pitts by explaining them in the context of automata theory and the theory of computa... |

32 | Tools for Formal Specification, Verification, and Validation of Requirements - Heitmeyer, Kirby, et al. |

29 | Java PathExplorer – A runtime verification tool - Havelund, Ro¸su - 2001 |