Artificial Neural Networks: Formal Models and Their Applications – ICANN 2005

Volume 3697 of the series Lecture Notes in Computer Science pp 533-539

Counterpropagation with Delays with Applications in Time Series Prediction

  • Carmen FierascuAffiliated withInstitute of Scientific Computing, University of Salzburg

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The paper presents a method for time series prediction using a complete counterpropagation network with delay kernels. Our network takes advantage of the clustering and mapping capability of the original CPN combined with dynamical elements and become able to discover and approximate the strongest topological and temporal relationships among the fields in the data. Experimental results using two chaotic time series and a set of astrophysical data validate the performance of the proposed method.