Some Networks That Can Learn, Remember, and Reproduce any Number of Complicated Space-Time Patterns, I

By Stephen Grossberg. 1969

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Citations in the corpus

Deep learning in neural networks: An overview (2014, background): “…following decades brought simple NNs trained by SL (e.g., Narendra & Thathatchar, 1974; Rosenblatt, 1958, 1962; Widrow & Hoff, 1962) and UL (e.g., Grossberg, 1969; Kohonen, 1972; von der Malsburg, 1973; Willshaw & von der Malsburg, 1976), as well as closely related associative memories (e.g.,…”
Laminar selectivity of the cholinergic suppression of synaptic transmission in rat hippocampal region CA1: computational modeling and brain slice physiology (1994, background): “A learning rule of this sort has been suggested previously on the basis of experimental data (Levy et al., 1990) and for stability during learning in analytical descriptions (Grossberg, 1976).”
Toward a modern theory of adaptive networks: expectation and prediction. (1981, methodology): “It may well be true that in the brain some kinds of temporal patterns are processed by being represented spatially, as, for example, suggested by Lashley (1951), and some models use this principle (e.g., Fukushima, 1973; Grossberg, 1969; Spinelli, 1970).”
The spatial coding model of visual word identification. (2010, background): “The waves are shown at a point in time soon after the p letter node has output its signal. avalanche network (Grossberg, 1969) could implement the serial scan.”
Nonlinear neural networks: Principles, mechanisms, and architectures (1988, background): “…neural networks defined by nonlinearly coupled STM and LTM traces, and to the mathematical proof that the computational units of these networks are not individual STM and LTM variables, but are rather distributed spatial patterns of STM and LTM variables (Grossberg, 1968b, 1969a, 1969b, 1970a).”
Adaptive pattern classification and universal recoding: I. Parallel development and coding of neural feature detectors (1976, background): “Grossberg (1970b) shows that the problem can be avoided by inhibiting each signal Kij irit gets too large.”
Neural syntax: cell assemblies, synapsembles and readers (2010, unknown): “However, experimental identification of the hypothesized cell assemblies has proven notoriously difficult (Gerstein et al., 1989; Grossberg, 1969; Ikegaya et al., 2004; Lansner, 2009; Neuron 68, November 4, 2010 ª2010 Elsevier Inc. Milner, 1957, 1996; Palm, 1982, 1987; Pouget et al., 2000;…”