By Ad Aertsen (auth.), Stan Gielen, Bert Kappen (eds.)
ISBN-10: 1447120639
ISBN-13: 9781447120636
ISBN-10: 3540198393
ISBN-13: 9783540198390
This ebook includes the court cases of the overseas Confer ence on synthetic Neural Networks which used to be held among September thirteen and sixteen in Amsterdam. it's the 3rd in a chain which began years in the past in Helsinki and which final yr came about in Brighton. due to the eu Neural community Society, ICANN has emerged because the best convention on neural networks in Europe. Neural networks is a box of study which has loved a swift growth and nice recognition in either the tutorial and business examine groups. the sector is stimulated by way of the widely held trust that functions within the fields of man-made intelligence and robotics will take advantage of a very good realizing of the neural info processing houses that underlie human intelligence. crucial points of neural info processing are hugely parallel execution of com putation, integration of reminiscence and technique, and robustness opposed to fluctuations. it really is believed that clever talents, resembling belief, movement and cognition, might be more straightforward learned in neuro-computers than in a standard computing paradigm. This calls for energetic learn in neurobiology to extract com putational rules from experimental neurobiological locate ings, in physics and arithmetic to check the relation among structure and serve as in neural networks, and in cognitive technology to review larger mind services, comparable to language and reasoning. Neural networks know-how has already bring about functional tools that resolve actual difficulties in a large sector of business purposes. The clusters on robotics and purposes include classes on a number of sub-topics in those fields.
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Additional info for ICANN ’93: Proceedings of the International Conference on Artificial Neural Networks Amsterdam, The Netherlands 13–16 September 1993
Example text
Whatever the underlying mechanisms, the experimentally observed, stimulus-driven and behavior-related modulations of functional coupling form an interesting feature of cortical organization. They are the signature of an ongoing process of dynamical and activity-related 'linking' and 'unlinking' of neurons in the cortical network. This process may have interesting functional implications at different levels of observation. At the single-neuron level, it might explain how even little speciflcity in anatomical connections could be dynamically sorted out to yield the complex functional properties that have been observed for cortical neurons.
Time-consuming Monte Carlo simulations can be avoided by' finding a single locally optimal point in weight space and constructing a full covariance Gaussian approximation to the posterior distribution around that point. The alternative method proposed in this paper is to use a simpler Gaussian approximation (with no off-diagonal terms in the covariance matrix) but to take this distribution into account during the leaming. With one layer of non-linear hidden units, the integration over the Gaussian distribution can be performed exactly and the exact weight derivatives can be computed efficiently.
Proc. Natl. Acad. Sci. USA 87: 7200-7204 49. Sompolinsky H, Golomb D, Kleinfeld D (1991) Cooperative dynamics in visual processing. Physical Rev A 43: 6990-7011 50. Sporns 0, Gally JA, Reeke GN Jr, Edelman GM, (1989) Reentrant signaling among simulated neuronal groups leads to coherency in their oscillatory avtivity. Proc Nat! Acad Sci USA 86: 7265-7269 51. Scbillen TB, Konig P (1991) Stimulus-dependent assembly formation of oscillatory responses. 2: Desynchronisation. Neural Comp 3: 167-178 52.
ICANN ’93: Proceedings of the International Conference on Artificial Neural Networks Amsterdam, The Netherlands 13–16 September 1993 by Ad Aertsen (auth.), Stan Gielen, Bert Kappen (eds.)
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