Investigating Fault Tolerance in ArtificialNeural Networks

.............................................................................................................................................. iii Section

[1]  W. R. Moore Conventional fault-tolerance and neural computers , 1988 .

[2]  D. Amit,et al.  Statistical mechanics of neural networks near saturation , 1987 .

[3]  James S. Albus,et al.  New Approach to Manipulator Control: The Cerebellar Model Articulation Controller (CMAC)1 , 1975 .

[4]  Terrence J. Sejnowski,et al.  Network model of shape-from-shading: neural function arises from both receptive and projective fields , 1988, Nature.

[5]  Terrence J. Sejnowski,et al.  A Parallel Network that Learns to Play Backgammon , 1989, Artif. Intell..

[6]  H. A. Mallot,et al.  Parallelism and redundancy in neural networks , 1989 .

[7]  Patrick Gallinari,et al.  EVALUATION OF NETWORK ARCHITECTURES ON TEST LEARNING TASKS. , 1987 .

[8]  Santosh S. Venkatesh,et al.  The capacity of the Hopfield associative memory , 1987, IEEE Trans. Inf. Theory.

[9]  Y S Abu-Mostafa,et al.  Neural networks for computing , 1987 .

[10]  Marc Mézard,et al.  Basins of Attraction in a Perception-like Neural Network , 1988, Complex Syst..

[11]  James A. Anderson,et al.  Cognitive and psychological computation with neural models , 1983, IEEE Transactions on Systems, Man, and Cybernetics.

[12]  Örjan Ekeberg,et al.  Reliability and Speed of Recall in an Associative Network , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  J. Goodman,et al.  Neural networks for computation: number representations and programming complexity. , 1986, Applied optics.

[14]  J J Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.

[15]  S. Kauffman Metabolic stability and epigenesis in randomly constructed genetic nets. , 1969, Journal of theoretical biology.

[16]  Paul Ammann,et al.  Data Diversity: An Approach to Software Fault Tolerance , 1988, IEEE Trans. Computers.

[17]  S. Venkatesh Epsilon capacity of neural networks , 1987 .

[18]  Risto Miikkulainen,et al.  Natural Language Processingwith Modular Neural Networks and Distributed Lexicon , 1991 .

[19]  Carver A. Mead,et al.  VLSI architectures for implementation of neural networks , 1987 .

[20]  T. R. Damarla,et al.  Fault tolerance of neural networks , 1989, Proceedings. IEEE Energy and Information Technologies in the Southeast'.

[21]  David Haussler,et al.  What Size Net Gives Valid Generalization? , 1989, Neural Computation.

[22]  W S McCulloch,et al.  A logical calculus of the ideas immanent in nervous activity , 1990, The Philosophy of Artificial Intelligence.

[23]  Harry Wechsler,et al.  FAULT-TOLERANT RECOGNITION USING DAM'S. , 1987 .

[24]  C. C. Wood,et al.  23 – Implications of Simulated Lesion Experiments for the Interpretation of Lesions in Real Nervous Systems , 1982 .

[25]  Geoffrey E. Hinton,et al.  Phoneme recognition using time-delay neural networks , 1989, IEEE Trans. Acoust. Speech Signal Process..

[26]  Charles R. Legéndy,et al.  On the scheme by which the human brain stores information , 1967 .

[27]  J. C. Pemberton,et al.  The effect of training signal errors on node learning , 1989, International 1989 Joint Conference on Neural Networks.

[28]  George H. Maestri The retryable processor , 1972, AFIPS '72 (Fall, part I).

[29]  Bernard Widrow,et al.  Punish/Reward: Learning with a Critic in Adaptive Threshold Systems , 1973, IEEE Trans. Syst. Man Cybern..

[30]  Donald F. Specht,et al.  Probabilistic neural networks , 1990, Neural Networks.

[31]  Marvin Minsky,et al.  Perceptrons: An Introduction to Computational Geometry , 1969 .

[32]  D. J. Wallace,et al.  Learning and memory properties in fully connected networks , 1987 .

[33]  Geoffrey E. Hinton,et al.  Learning internal representations by error propagation , 1986 .

[34]  Michael J. Carter,et al.  Operational Fault Tolerance of CMAC Networks , 1989, NIPS.

[35]  Y. Malaiya Fault Modeling , 1985, IEEE Design & Test of Computers.

[36]  S. Y. Kung,et al.  Parallel architectures for artificial neural nets , 1988, IEEE 1988 International Conference on Neural Networks.

[37]  Y. S. Abu-Mostafa Complexity of random problems , 1988 .