Aart, E. and Korst, J. (1989). Simulated Annealing
and Boltzmann Machines. Wiley, New York.
Abu-Mostafa, Y. S. (1986a). "Neural Networks for
Computing?" in Neural Networks for Computing, J. S. Denker,
Editor, 151, 1-6. American Institute of Physics, New York.
Abu-Mostafa, Y. S. (1986b). "Complexity of Random
Problems," in Complexity in Information Theory, Y. Abu-Mostafa,
Editor, 115-131. Springer-Verlag, Berlin.
Abu-Mostafa, Y. S. and Psaltis, D. (1987). "Optical
Neural Computers," Scientific American, 256(3), 88-95.
Abu Zitar, R. A. (1993). Machine Learning with Rule Extraction
by Genetic Assisted Reinforcement (REGAR): Application to Nonlinear Control.
Ph.D. Dissertation, Department of Electrical and Computer Engineering,
Wayne State University, Detroit, Michigan.
Abu Zitar, R. A. and Hassoun, M. H. (1993a). "Neurocontrollers
Trained with Rules Extracted by a Genetic Assisted Reinforcement Learning
System," IEEE Transactions on Neural Networks, to appear in
Abu Zitar, R. A. and Hassoun, M. H. (1993b). "Regulator
Control via Genetic Search Assisted Reinforcement," in Proceedings
of the Fifth International Conference on Genetic Algorithms (Urbana-Champaign
1993), S. Forrest, Editor, 254-262. Morgan Kaufmann, San Mateo.
Ackley, D. H. and Littman, M. S. (1990). "Generalization
and Scaling in Reinforcement Learning," in Advances in Neural Information
Processing II (Denver 1989), D. S. Touretzky, Editor, 550-557. Morgan
Kaufmann, San Mateo.
Ackley, D. H., Hinton, G. E., and Sejnowski, T. J. (1985).
"A Learning Algorithm for Boltzmann Machines," Cognitive Science,
Alander, J. T. (1992). "On Optimal Population Size
of Genetic Algorithms," Proceedings of CompEuro 92 (The Hague,
Netherlands 1992), 65-70. IEEE Computer Society Press, New York.
Albert, A. (1972). Regression and the Moore-Penrose
Pseudoinverse. Academic Press, New York, NY.
Albus, J. S. (1971). "A Theory of Cerebellar Functions,"
Mathematical Biosciences, 10, 25-61.
Albus, J. S. (1975). "A New Approach to Manipulator
Control: The Cerebellar Model Articulation Controller (CMAC)," Journal
of Dynamic Systems Measurement and Control, Transactions of the ASME,
Albus, J. S. (1979). "A Model of the Brain for Robot
Control, Part 2: A Neurological Model," BYTE, 54-95.
Albus, J. S. (1981). Brains, Behavior, and Robotics.
Alkon, D. L., Blackwell, K. T., Vogl, T. P., and Werness,
S. A. (1993). "Biological Plausibility of Artificial Neural Networks:
Learning by Non-Hebbian Synapses," in Associative Neural Memories:
Theory and Implementation, M. H. Hassoun, Editor, 31-49. Oxford University
Press, New York.
Almeida, L. B. (1987). "A Learning Rule for Asynchronous
Perceptrons with Feedback in a Combinatorial Environment," in IEEE
First International Conference on Neural Networks (San Diego 1987),
M. Caudill and C. Butler, Editors, vol. II, 609-618. IEEE, New York.
Almeida, L. B. (1988). "Backpropagation in Perceptrons
with Feedback," in Neural Computers (Neuss 1987), R. Eckmiller
and C. von der Malsburg, Editors, 199-208. Springer-Verlag, Berlin.
Alspector, J. and Allen, B. B. (1987). "A Neuromorphic
VLSI Learning System," in Advanced Research in VLSI: Proceedings
of the 1987 Stanford Conference, P. Losleben, Editor, 313-349. MIT,
Aluffi-Pentini, F., Parisi, V., and Zirilli, F. (1985).
"Global Optimization and Stochastic Differential Equations,"
Journal of Optimization Theory and Applications, 47(1), 1-16.
Amari, S.-I. (1967). "Theory of Adaptive Pattern
Classifiers," IEEE Trans. Electronic Computers, EC-16,
Amari, S.-I. (1968). Geometrical Theory of Information.
In Japanese. Kyoritsu-Shuppan, Tokyo.
Amari, S.-I. (1971). "Characteristics of Randomly
Connected Threshold-Element Networks and Network Systems," IEEE
Proc., 59(1), 35-47.
Amari, S.-I. (1972a). "Learning Patterns and Pattern
Sequences by Self-Organizing Nets of Threshold Elements," IEEE
Trans. Computers, C-21, 1197-1206.
Amari, S.-I. (1972b). "Characteristics of Random
Nets of Analog Neuron-Like Elements," IEEE Transactions on Systems,
Man, and Cybernetics, SMC-2(5), 643-657.
Amari, S.-I. (1974). "A Method of Statistical Neurodynamics,"
Kybernetik, 14, 201-215.
Amari, S.-I. (1977a). "Neural Theory of Association
and Concept-Formation," Biological Cybernetics, 26,
Amari, S.-I. (1977b). "Dynamics of Pattern Formation
in Lateral-Inhibition Type Neural Fields," Biological Cybernetics,
Amari, S.-I. (1980). "Topographic Organization of
Nerve Fields," Bull. of Math. Biology, 42, 339-364.
Amari, S.-I. (1983). "Field Theory of Self-Organizing
Neural Nets," IEEE Trans. Syst., Man, Cybernetics, SMC-13,
Amari, S.-I. (1989). "Characteristics of Sparsely
Encoded Associative Memory," Neural Networks, 2(6),
Amari, S.-I. (1990). "Mathematical Foundations of
Neurocomputing," Proceedings of the IEEE, 78(9), 1443-1463.
Amari, S.-I. (1993). "A Universal Theorem on Learning
Curves," Neural Networks, 6(2), 161-166.
Amari, S.-I., Fujita, N., and Shinomoto, S. (1992). "Four
Types of Learning Curves," Neural Computation, 4(2),
Amari, S.-I. and Maginu, K. (1988). "Statistical
Neurodynamics of Associative Memory," Neural Networks, 1(1),
Amari, S.-I. and Murata, N. (1993). "Statistical
Theory of Learning Curves Under Entropic Loss Criterion," Neural
Computation, 5(1), 140-153.
Amari, S.-I. and Yanai, H.-F. (1993). "Statistical
Neurodynamics of Various Types of Associative Nets," in Associative
Neural Memories: Theory and Implementation, M. H. Hassoun, Editor,
169-183. Oxford University Press, New York.
Amit, D. J. (1989). Modeling Brain Function: The World
of Attractor Neural Networks. Cambridge University Press, Cambridge.
Amit, D. J., Gutfreund, H., and Sompolinsky, H. (1985).
"Storing Infinite Numbers of Patterns in a Spin-Glass Model of Neural
Networks," Physical Review Lett., 55(14), 1530-1533.
Amit, D. J., Gutfreund, H., and Sompolinsky, H. (1987).
"Statistical Mechanics of Neural Networks Near Saturation," Ann.
Phys. N. Y., 173, 30-67.
Anderberg, M. R. (1973). Cluster Analysis for Applications.
Academic Press, NY.
Anderson, J. A. (1972). "A Simple Neural Network
Generating Interactive Memory," Mathematical Biosciences, 14,
Anderson, J. A. (1983). "Neural Models for Cognitive
Computations," IEEE Transactions on Systems, Man, and Cybernetics,
Anderson, J. A. (1993). "The BSB Model: A Simple
Nonlinear Autoassociative Neural Network," in Associative Neural
Memories: Theory and Implementation, M. H. Hassoun, Editor, 77-103.
Oxford University Press, New York.
Anderson, D. Z. and Erie, M. C. (1987). "Resonator
Memories and Optical Novelty Filters," Optical Engineering,
Anderson, J. A., Gately, M. T., Penz, P. A., and Collins,
D. R. (1990). "Radar Signal Categorization Using a Neural Network,"
Proc. IEEE, 78, 1646-1657.
Anderson, J. A. and Murphy, G. L. (1986). "Psychological
Concepts in a Parallel System," Physica, 22-D, 318-336.
Anderson, J. A., Silverstien, J. W., Ritz, S. A., and
Jones, R. S. (1977). "Distinctive Features, Categorical Perception,
and Probability Learning: Some Applications of a Neural Model," Psychological
Review, 84, 413-451.
Angeniol, B., Vaubois, G. and Le Texier, Y.-Y. (1988).
"Self-Organizing Feature Maps and the Traveling Salesman Problem,"
Neural Networks, 1(4), 289-293.
Apolloni, B. and De Falco, D. (1991). "Learning by
Asymmetric Parallel Boltzmann Machines." Neural Computation,
Apostol, T. M. (1957). Mathematical Analysis: A Modern
Approach to Advanced Calculus. Addison-Wesely, Reading, MA.