Applications of Neural Networks
Published on 30. September 1992
Book
Hardback
XV, 249 pages
978-3-527-29010-9 (ISBN)
Description
Succes in the field of neural networks and their real-world applications depends on the fruitful exchange of ideas of physicists, computer engineers and neurobiologists. This work provides this, placing emphasis on contributions from both academia and industry. Topics covered include speed and performance for online data processing, robotics and neural control systems, and neural networks for analysis and classification.
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Content
Part 1 Neuronal oscillations - physiological evidence: temporal coding by coherent oscillations as a potential solution to the binding problem, Andreas K.Engel, et al; temporal properties of synchronous oscillatory neuronal interactions in cat striate cortex, Charles M. Gray, et al; stimulus-related facilitation and synchronization among visual cortical areas - experiments and models, R. Eckhorn, et al; small nervous systems and neural network models, D. Kleinfeld, et al. Part 2 Neuronal oscillations - models and simulations: phase coherence and computation in a neural network of coupled oscillators, H. Sompolinsky, et al; nonlinear dynamics and neuronal oscillations, Heinz G. Schuster; dynamic interactions of neuronal groups and the problem of cortical integration, Olaf Sporns, et al; temporal coding by coherent oscillations as a potential solution to the binding problem - neural network simulations, Thomas B. Schillen and Peter Konig; phase-locking in 1-D and 2-D networks of oscillating neurons, Ernst Niebuhr, et al. Part 3 State variables, assemblies and data analysis: what are the state variables for modelling brain dynamics with neural networks?, Walter J. Freeman; new descriptors for the activity of brain cell assemblies - requirements and opportunities, Theodore H. Bullock; cellular assemblies and the dynamics of cortical minicolumns, Steen S. Christensen, et al; dynamics of activity and connectivity in physiological neuronal networks, Ad Aertsen and Hubert Preibl. Part 4 Self-organization and high level representations: distributed hypothesis testing, attention shifts, and transmitter dynamics during self-organization of brain recognition codes, Gail A. Carpenter and Stephen Grossberg; high-level representations of space and movement in neural networks controlling motor behaviour, Klaus Hepp.