References
- Amit D J, Gutfreund H, Sompolinsky H. Spin-glass models of neural networks. Phys. Rev. 1985; A 32: 1007
- Amit D J. Modeling Brain Function. Cambridge University Press, Cambridge 1989
- Gardner E J. The space of interactions in neural network models. J. Phys. A: Math. Gen. 1987; 20: 257
- Hartstein A, Koch R H. A self-learning threshold-controlled neural network. IEEE Int. Joint Conf. on Neural Networks. San Diego. IEEE, Piscataway, NJ 1988; I-425-30
- Hartstein A. The role of dimensionality in a threshold-controlled neural network. Network: Computation in Neural Systems 1991; 2: 125–9
- Holler M, Tam S, Castro H, Benson R. An electrically trainable artificial neural network (ETANN). IEEE Int. Joint Conf. Neural Networks. Washington. IEEE, Piscataway, NJ 1989; II-191-6
- Holler M. VLSI implementations of learning and memory systems. Advances in Neural Information Processing Systems, R P Lippman, J Moody, D Touretsky. Morgan Kaufmann, San Mateo, CA 1991; 3: 993–1000
- Hopfield J J. Neural networks and physical systems with emergent collective computational abilities. Proc. Natl Acad. Sci. USA 1982; 79: 2554–58
- Hopfield J J. Neurons with graded response have collective computational properties like those of two-state neurons. Proc. Natl Acad. Sci. USA 1982; 81: 3088–92
- Kanerva P. Sparse Distributed Memory. MIT Press, Cambridge, MA 1989
- Kanter I, Sompolinsky H. Associative recall of memory without errors. Phys. Rev. 1986; A 35: 380
- Lapedes A, Farber R. Nonlinear signal processing using neural networks. Report. Los Alamos Natl Lab. 1987, LA-UR-87-2662
- Lapedes A, Farber R. How neural nets work. Proc. 1987 Conf. on Neural Information Processing Systems. Anderson. 1988; 442–56
- Le Cun Y. Une procedure d'apprentissge pour reseau a seuil assymetrique. Proc. Cognitiva '85. Paris, 1985; 599–604
- Lippman R P. An introduction to computing with neural nets. IEEE ASSP Magazine April, 1987; 4–22
- Marcus C M, Westervelt R M. Dynamics of iterated-map neural networks. Phys. Rev. 1989; A 40: 501–4
- McCullough W, Pitts W. A logical calculus of the ideas immanent in nervous activity. Bull. Math. Biophys. 1943; 5: 115–33
- Mead C A. Analog VLSI and Neural Systems. Addison-Wesley, Reading, MA 1989
- Moody J, Darken C. Learning with localized receptive fields. Proc. 1988 Connectionist Models Summer School, Touretsky D, G Hinton, T J Sejnowski. Morgan Kaufmann, San Mateo, CA 1988; 133–43
- Morgan D P, Scofield C L. Neural Networks and Speech Processing. Kluwer, Boston, MA 1991
- Nestor Inc. Annual Report. Nestor, Providence, RI 1990
- Parker D B. Learning-logic. Report. MIT Cen. Computational Res. Economics Management Sci. 1985, TR-47
- Park C S, Castro H. Exclusive-or cell for pattern matching employing floating gate devices. US Patent 1991; 4,999,525, (Analogue designs employing the same principles have patents pending.)
- Poggio T, Girosi F. Regularization algorithms for learning that are Equivalent to multilayer networks. Science 1990; 247: 978–82
- Reilly D L, Cooper L N, Elbaum C. A neural model for category learning. Biol. Cybern. 1982; 45: 35–41
- Rosenblatt F. The perceptron: a probabilistic model for information storage and organization in the brain. Pysch. Rev. 1958; 65: 386–408
- Rumelhart D, Hinton D, Williams G. Learning internal representations by error backpropagation. Parallel Distributed Processing, D. Rumelhart, J L McClelland. MIT Press, Cambridge, MA 1986; 1: 318–64
- Sherrington D. Special issue in memory of Elizabeth Gardner 1957-1988. J. Phys. A: Math. Gen. 1989; 22: 1955–2273
- Werbos P. Beyond regression: New tools for prediction and analysis in the behavioral sciences PhD Dissertation. Committee on Applied Mathematics, Harvard University. 1974
- Widrow B, Hoff M E. Adaptive switching circuits. Tech. Rep. 1553-1. Stanford Electron. Labs. 1960