Titlebook: Dealing with Complexity; A Neural Networks Ap Mirek Kárny,Kevin Warwick,Vera K?rková Book 1998 Springer-Verlag London Limited 1998 artifici

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Recent Results and Mathematical Methods for Functional Approximation by Neural Networks,weights” .. When the input dimension is . and the output dimension is 1, .: R. → .. For example, if . is the standard perceptron architecture with activation function . hidden units and 1 linear output unit, then for . composed of the v., .. and .. below, one has the usual expression ., where ..∈ .. and .., ..∈ .. are the parameters.

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The Psychological Limits of Neural Computation, the Church-Turing thesis, .. is also the class of algorithmic computable sets. In spite of its generality, the Turing model . solve any problem. Recall, for example, that the halting problem is Turing unsolvable: it is algorithmic undecidable if an arbitrary Turing machine will eventually halt when given some specified, but arbitrary, input.

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Numerical Aspects of?Hyperbolic Geometry observed sample, to guess what values an unobserved quantity may have, to predict what values of some quantities will occur, to guess the state of a patient or a technical system, to select values of manipulable variables fed into a controlled system etc.

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Statistical Decision Making and Neural Networks, observed sample, to guess what values an unobserved quantity may have, to predict what values of some quantities will occur, to guess the state of a patient or a technical system, to select values of manipulable variables fed into a controlled system etc.

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Incremental Approximation by Neural Networks,d various types of such architecture dynamics in which network units or connections are either added or deleted. The simplest type is . where in each step an architecture is extended by adding one new unit.

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