Proceedings ArticleDOI
Associative Learning, Adaptive Pattern Recognition, And Cooperative-Competitive Decision Making By Neural Networks
Gail A. Carpenter,Stephen Grossberg +1 more
- Vol. 0634, pp 218-247
TLDR
In this article, the authors describe models of associative pattern learning, adaptive pattern recognition, and parallel decision-making by neural networks and show that a small set of real-time non-linear neural equations within a larger set of specialized neural circuits can be used to study a wide variety of such problems.Abstract:
This article describes models of associative pattern learning, adaptive pattern recognition, and parallel decision-making by neural networks. It is shown that a small set of real-time non-linear neural equations within a larger set of specialized neural circuits can be used to study a wide variety of such problems. Models of energy minimization, cooperative-competitive decision making, competitive learning, adaptive resonance, interactive activation, and back propagation are discussed and compared.read more
Citations
More filters
Journal ArticleDOI
Bidirectional associative memories
TL;DR: The author proves that every n-by-p matrix M is a bidirectionally stable heteroassociative content-addressable memory for both binary/bipolar and continuous neurons.
Book ChapterDOI
Theory of the backpropagation neural network
TL;DR: A speculative neurophysiological model illustrating how the backpropagation neural network architecture might plausibly be implemented in the mammalian brain for corticocortical learning between nearby regions of the cerebral cortex is presented.
Proceedings ArticleDOI
Theory of the backpropagation neural network
TL;DR: A speculative neurophysiological model illustrating how the backpropagation neural network architecture might plausibly be implemented in the mammalian brain for corticocortical learning between nearby regions of the cerebral cortex is presented.
Journal ArticleDOI
Nonlinear neural networks: Principles, mechanisms, and architectures
TL;DR: An historical discussion is provided of the intellectual trends that caused nineteenth century interdisciplinary studies of physics and psychobiology by leading scientists such as Helmholtz, Maxwell, and Mach to splinter into separate twentieth-century scientific movements.
Journal ArticleDOI
Neural networks: algorithms, applications, and programming techniques
TL;DR: The authors survey the most common neural-network architectures and show how neural networks can be used to solve actual scientific and engineering problems and describe methodologies for simulating neural- network architectures on traditional digital computing systems.