Book Review
The AMS does not provide abstracts of book reviews.
You may download the entire review from the links below.
Full text of review:
PDF
Book Information
Author:
Clark Jeffries
Title:
Code recognition and set selection with neural networks
Additional book information
Birk\h\"auser, Boston, 1991, 166 pp., US$49.50. ISBN 0817635858.
 [1]
J. Anderson and E. Rosenfeld (eds.), Neurocomputing: Foundations of research, MIT Press, Cambridge, MA, 1988.
 [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 AIPConf. 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 higherorder neural networks, Appl. Optics 26 (1987), 49724978.
 [6]
S. Grossberg, The adaptive brain, Advances in Psychology, NorthHolland, New York, 1987.
 [7]
S. Grossberg and M. Kuperstein, Neural dynamics of adaptive sensorymotor control, Pergamon Press, New York, 1989.
 [8]
R. HechtNielsen, Neurocomputing, AddisonWesley, 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, AddisonWesley, Reading, MA, 1991.
 [10]
J.
J. Hopfield, Neural networks and physical systems with emergent
collective computational abilities, Proc. Nat. Acad. Sci. U.S.A.
79 (1982), no. 8, 2554–2558. MR 652033
(83g:92024)
 [11]
, Neurons with graded responses have collective computational properties like those of twostate neurons, Nat. Acad. Sci. U.S.A. 81 (1984), 39883092.
 [12]
J. Kidder, A theory of faulty vector fields, Ph.D. thesis, Univ. of California at Berkeley, 1992.
 [13]
T. Kohonen, Contentaddressable memories, SpringerVerlag, New York, 1980.
 [14]
D. Levine, Introduction to neural and cognitive modeling, L. Erlbaum Associates, Hillsdale, NJ, 1991.
 [15]
Warren
S. McCulloch and Walter
Pitts, A logical calculus of the ideas immanent in nervous
activity, Bull. Math. Biophys. 5 (1943),
115–133. MR 0010388
(6,12a)
 [16]
C. Mead, Analog VLSI and neural systems, AddisonWesley, Reading, MA, 1989.
 [17]
M. Minsky and S. Papert, Perceptrons; an introduction to computational geometry, expanded ed., MIT Press, Cambridge, MA, 1988.
 [18]
Frank
Rosenblatt, Principles of neurodynamics. Perceptrons and the theory
of brain mechanisms, Spartan Books, Washington, D.C., 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), 145168.
 [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), 161195.
 [22]
B. Widrow, Generalization and information storage in networks of adaline "neurons", SelfOrganizing Systems 1962 (M. Yovits, G. Jacobi, and G. Goldstein, eds.), Spartan Books, Washington, DC, 1962, pp. 435461.
 [23]
B. Widrow and M. Hoff, Adaptive switching circuits, Neurocomputing (J. Anderson and E. Rosenfeld, eds.), MIT Press, Cambridge, MA, 1988.
 [1]
 J. Anderson and E. Rosenfeld (eds.), Neurocomputing: Foundations of research, MIT Press, Cambridge, MA, 1988.
 [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 AIPConf. 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 higherorder neural networks, Appl. Optics 26 (1987), 49724978.
 [6]
 S. Grossberg, The adaptive brain, Advances in Psychology, NorthHolland, New York, 1987.
 [7]
 S. Grossberg and M. Kuperstein, Neural dynamics of adaptive sensorymotor control, Pergamon Press, New York, 1989.
 [8]
 R. HechtNielsen, Neurocomputing, AddisonWesley, 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, AddisonWesley, 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), 25542558. MR 652033 (83g:92024)
 [11]
 , Neurons with graded responses have collective computational properties like those of twostate neurons, Nat. Acad. Sci. U.S.A. 81 (1984), 39883092.
 [12]
 J. Kidder, A theory of faulty vector fields, Ph.D. thesis, Univ. of California at Berkeley, 1992.
 [13]
 T. Kohonen, Contentaddressable memories, SpringerVerlag, 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), 115133. MR 0010388 (6:12a)
 [16]
 C. Mead, Analog VLSI and neural systems, AddisonWesley, 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), 145168.
 [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), 161195.
 [22]
 B. Widrow, Generalization and information storage in networks of adaline "neurons", SelfOrganizing Systems 1962 (M. Yovits, G. Jacobi, and G. Goldstein, eds.), Spartan Books, Washington, DC, 1962, pp. 435461.
 [23]
 B. Widrow and M. Hoff, Adaptive switching circuits, Neurocomputing (J. Anderson and E. Rosenfeld, eds.), MIT Press, Cambridge, MA, 1988.
Review Information
Reviewer:
Morris W. Hirsch
Journal:
Bull. Amer. Math. Soc. 29 (1993), 256262
DOI:
http://dx.doi.org/10.1090/S027309791993004117
PII:
S 02730979(1993)004117
