Read e-book online 4th Neural Computation and Psychology Workshop, London, 9–11 PDF

By Mike Page (auth.), John A. Bullinaria BSc, MSc, PhD, David W. Glasspool BSc, Msc, George Houghton BA, MSc, PhD (eds.)

ISBN-10: 1447115465

ISBN-13: 9781447115465

ISBN-10: 3540762086

ISBN-13: 9783540762089

This quantity collects jointly refereed types of twenty-five papers awarded on the 4th Neural Computation and Psychology Workshop, held at college collage London in April 1997. The "NCPW" workshop sequence is now good verified as a full of life discussion board which brings jointly researchers from such various disciplines as synthetic intelligence, arithmetic, cognitive technological know-how, desktop technological know-how, neurobiology, philosophy and psychology to debate their paintings on connectionist modelling in psychology. the overall topic of this fourth workshop within the sequence used to be "Connectionist Repre­ sentations", a subject which not just attracted contributors from these types of fields, yet from allover the realm to boot. From the viewpoint of the convention organisers targeting representational concerns had the virtue that it instantly concerned researchers from all branches of neural computation. Being so valuable either to psychology and to connectionist modelling, it really is one zone approximately which each person within the box has their very own robust perspectives, and the range and caliber of the displays and, simply as importantly, the dialogue which them, definitely attested to this.

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Additional info for 4th Neural Computation and Psychology Workshop, London, 9–11 April 1997: Connectionist Representations

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The number of RBF hidden nodes increases exponentially with the input space dimensionality so that RBF is time-consuming if the number of inputs is large. In this case, MLP is preferred to RBF but CSFN is better than either alternative. 2 Conic sections Conic sections are the shapes obtained when a right circular cone, which has its vertex above the centre of its base, is cut along a plane at various angles to the cone's axes. In other words, the conic sections are formed from the intersection between a cone and a plane.

2 Delaunay Triangulations, Voronoi Diagrams In Computational Geometry the formal definition of the Delaunay Triangulation (DT) of a set of points belonging to an N-dimension space is usually stated in terms of its dual association with another important geometric form, the Voronoi Diagram (VD). The two constructs are a type of tessellation [2] whose main distinguishing property is that both are totally derived from the data. The VD generated from a set of M points, {Pl,P2, ... ,Pk, ... ,PM} in N-dimension space, called sites, corresponds to a partition of the space into 50 Figure 2: Voronoi Diagram, Delaunay Triangulation of the input domain convex regions, called Voronoi cells.

The network has again extracted two of the prototypes as centre vectors, but now ignores some of the inputs. In particular, two of the inputs (7 and 9) in centre 1 are ignored so that this REF acts as a feature detector rather than a template matcher. 5 Localist and Distributed Representations Together? REF networks pay attention to areas of input space detennined by their vectors. They also pay attention to individual dimensions in the input detennined by their nonn weights. The REF network is therefore able to both template or exemplar based accounts of categorization, and feature accounts.

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4th Neural Computation and Psychology Workshop, London, 9–11 April 1997: Connectionist Representations by Mike Page (auth.), John A. Bullinaria BSc, MSc, PhD, David W. Glasspool BSc, Msc, George Houghton BA, MSc, PhD (eds.)

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