论文信息 - The basic ideas in neural networks

The basic ideas in neural networks

Interest in the study of neural networks has grown remarkably in the last several years. This effort has been characterized in a variety of ways: as the study of brain-style computation, connectionist architectures, parallel distributed-processing systems, neuromorphic computation, artificial neural systems. The common theme to these efforts has been an interest in looking at the brain as a model of a parallel computational device very different from that of a traditional serial computer

Bernard Widrow | David E. Rumelhart | Michael A. Lehr | D. Rumelhart | B. Widrow

[1] O. G. Selfridge,et al. Pattern recognition and modern computers , 1899, AFIPS '55 (Western).

[2] A. A. Mullin,et al. Principles of neurodynamics , 1962 .

[3] P. Werbos,et al. Beyond Regression : "New Tools for Prediction and Analysis in the Behavioral Sciences , 1974 .

[4] 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.

[5] Stephen Grossberg,et al. Absolute stability of global pattern formation and parallel memory storage by competitive neural networks , 1983, IEEE Transactions on Systems, Man, and Cybernetics.

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

[7] Paul Smolensky,et al. Information processing in dynamical systems: foundations of harmony theory , 1986 .

[8] James L. McClelland,et al. Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .

[9] W. Pitts,et al. A Logical Calculus of the Ideas Immanent in Nervous Activity (1943) , 2021, Ideas That Created the Future.

[10] David E. Rumelhart,et al. Generalization by Weight-Elimination with Application to Forecasting , 1990, NIPS.