From: IN%"tenorio@dynamo.ecn.purdue.edu" "Manoel Fernando Tenorio" 29-NOV-1993 12:57:32.62 To: IN%"bras-nnet@dynamo.ecn.purdue.edu" CC: Subj: [: ] ------- Forwarded Message From: "R. Murray-Smith" Subject: IEE Colloq. Neural networks: CALL FOR PAPERS CALL FOR PAPERS --------------- IEE Colloquium on Advances in Neural Networks for Control and Systems 26-27 May 1994 To be held at a location in Central Europe A colloquium on `Advances in neural networks for control and systems' is being organised by the control committees of the Institution of Electrical Engineers with additional support from Daimler-Benz Systems Technology Research, Berlin. This two-day meeting will be held on 26-27 May 1994 at a central european location. The programme will comprise a mix of invited papers and papers received in response to this call. Invited speakers include leading international academic workers in the field and major industrial companies who will present recent applications of neural methods, and outline the latest theoretical advances. Neural networks have been seen for some years now as providing considerable promise for application in nonlinear control and systems problems. This promise stems from the theoretical ability of networks of various types to approximate arbitrarily well continuous nonlinear mappings. The aim of this colloquium is to evaluate the state-of-the-art in this very popular field from the engineering perspective. The colloquium will cover both theoretical and applied aspects. A major goal of the workshop will be to examine ways of improving the engineering involved in neural network modelling and control, so that the theoretical power of learning systems can be harnessed for practical applications. This includes questions such as: - Which network architecture for which application? - Can constructive learning algorithms capture the underlying dynamics while avoiding overfitting? - How can we introduce a priori knowledge or models into neural networks? - Can experiment design and active learning be used to automatically create 'optimal' training sets? - How can we validate a neural network model? In line with this goal of better engineering methods, the colloquium will also place emphasis on real industrial applications of the technology; applied papers are most welcome. Prospective authors are invited to submit three copies of a 500-word abstract by Friday 25 February 1994 to Dr K J Hunt, Daimler-Benz AG, Alt-Moabit 91 B, D-10559 Berlin, Germany (tel: + 49 30 399 82 275, FAX: + 49 30 399 82 107, E-mail: hunt@DBresearch-berlin.de). ------- End of Forwarded Message Return-path: Received: from ccsun.unicamp.br by ccvax.unicamp.br (PMDF #2801 ) id <01H5VYGZN9CW8WX3OV@ccvax.unicamp.br>; Mon, 29 Nov 1993 12:15:41 BSC (-0300 C) Received: from hermes.ecn.purdue.edu by ccsun.unicamp.br (4.1/SMI-4.0) id AA25754; Mon, 29 Nov 93 12:12:29 BSC Received: from dynamo.ecn.purdue.edu by hermes.ecn.purdue.edu (5.65/1.32jrs) id AA26289; Mon, 29 Nov 93 08:50:45 -0500 Received: from localhost by dynamo.ecn.purdue.edu (5.65/1.32jrs) id AA18779; Mon, 29 Nov 93 08:50:44 -0500 Date: 29 Nov 1993 08:50:43 -0500 (EST) From: Manoel Fernando Tenorio Subject: [: ] To: bras-nnet@dynamo.ecn.purdue.edu Message-id: <9311291350.AA18779@dynamo.ecn.purdue.edu> X-Envelope-to: infomed, sabbatini Content-transfer-encoding: 7BIT