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Bulletin of the American Mathematical Society
Bulletin of the American Mathematical Society
ISSN 1088-9485(e) ISSN 0273-0979(p)

     

Book Review

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Book Information

Author(s): Clark Jeffries
Title: Code recognition and set selection with neural networks
Additional book information: Birkh\"auser, Boston, 1991, 166 pp., US$49.50. ISBN 0-8176-3585-8


References:

[1]
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[2]
J. Anderson, R. Rosenfeld, and A. Pellionisz (eds.), Neurocomputing 2: Directions for research, MIT Press, Cambridge, MA, 1990.

[3]
H. H. Chen, Y. C. Lee, G. Z. Sun, H. Y. Lee, T. Maxwell, and C. L. Giles, High order correlation model for associative memory, Neural Networks for Computing AIP-Conf. Proc., vol. 151, Amer. Inst. Phys., New York, 1986, p. 86.

[4]
Stuart Cowan, Dynamical systems arising from game theory, Ph.D. thesis, Univ. of California at Berkeley, 1993.

[5]
C. Giles and T. Maxwell, Learning, invariance, and generalization in higher-order neural networks, Appl. Optics 26 (1987), 4972-4978.

[6]
S. Grossberg, The adaptive brain, Advances in Psychology, North-Holland, New York, 1987.

[7]
S. Grossberg and M. Kuperstein, Neural dynamics of adaptive sensory-motor control, Pergamon Press, New York, 1989.

[8]
R. Hecht-Nielsen, Neurocomputing, Addison-Wesley, Reading, MA, 1990.

[9]
J. Hertz, A. Krogh, and G. Palmer, Introduction to the theory of neural computation, Santa Fe Institute studies in the sciences of complexity, Lecture notes, vol. 1, Addison-Wesley, Reading, MA, 1991.

[10]
J. Hopfield, Neural networks and physical systems with emergent collective computational abilities, Proc. Nat. Acad. Sci U.S.A. 79 (1982), 2554-2558. MR 652033 (83g:92024)

[11]
-, Neurons with graded responses have collective computational properties like those of two-state neurons, Nat. Acad. Sci. U.S.A. 81 (1984), 3988-3092.

[12]
J. Kidder, A theory of faulty vector fields, Ph.D. thesis, Univ. of California at Berkeley, 1992.

[13]
T. Kohonen, Content-addressable memories, Springer-Verlag, New York, 1980.

[14]
D. Levine, Introduction to neural and cognitive modeling, L. Erlbaum Associates, Hillsdale, NJ, 1991.

[15]
W. McCulloch and W. Pitts, A logical calculus of ideas immanent in nervous activity, Bull. Math. Biophys. 5 (1943), 115-133. MR 0010388 (6:12a)

[16]
C. Mead, Analog VLSI and neural systems, Addison-Wesley, Reading, MA, 1989.

[17]
M. Minsky and S. Papert, Perceptrons; an introduction to computational geometry, expanded ed., MIT Press, Cambridge, MA, 1988.

[18]
F. Rosenblatt, Principles of neurodynamics; perceptrons and the theory of brain mechanisms, Spartan Books, Washington, DC, 1962. MR 0135635 (24:B1682)

[19]
D. Rumelhart, J. McClelland, and the PDP research group, Parallel distributed processing: explorations in the microstructure of cognition, vols. 1, 2, MIT Press, Cambridge, MA, 1986.

[20]
T. Sejnowski and C. Rosenberg, Parallel networks that learn to pronounce English text, Complex Systems 1 (1987), 145-168.

[21]
A. Skarda and W. J. Freeman, How brains make chaos in order to make sense of the world, Behavioral and Brain Science 10 (1987), 161-195.

[22]
B. Widrow, Generalization and information storage in networks of adaline "neurons", Self-Organizing Systems 1962 (M. Yovits, G. Jacobi, and G. Goldstein, eds.), Spartan Books, Washington, DC, 1962, pp. 435-461.

[23]
B. Widrow and M. Hoff, Adaptive switching circuits, Neurocomputing (J. Anderson and E. Rosenfeld, eds.), MIT Press, Cambridge, MA, 1988.


Additional Information:

Reviewer(s):
Morris W. Hirsch

Review Information:
Journal: Bull. Amer. Math. Soc. 29 (1993), 256-262.
DOI: 10.1090/S0273-0979-1993-00411-7
PII: S 0273-0979(1993)00411-7




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