Neurocomputing theory, practice and applications are the essential topics being covered. Neurocomputing welcomes theoretical contributions aimed at winning further understanding of neural networks and learning systems, including, but not restricted to, architectures, learning methods, analysis of network dynamics, theories of learning, self-organisation, biological neural network modelling, sensorimotor transformations and interdisciplinary topics with artificial intelligence, artificial life, cognitive science, computational learning theory, fuzzy logic, genetic algorithms, information theory, machine learning, neurobiology and pattern recognition. See Instructions and Background and Preliminary Citation Information. This page contains links to journals covering the topic of Neural Networks and Connectionism. Many of these links provide table of content listings for specific journals and descriptions about the journals.
Some links provide abstracts or entire articles in electronic form.
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