Abstract
In this paper we show, for the first time, how Radial Basis Function (RBF) network techniques can be used to explore questions surrounding authorship of historic documents. The paper illustrates the technical and practical aspects of RBF's, using data extracted from works written in the early 17th century by William Shakespeare and his contemporary John Fletcher. We also present benchmark comparisons with other standard techniques for contrast and comparison.
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David Lowe is Professor of Neural Computing at Aston University, UK. His research interests span from the theoretical aspects of dynamical systems theory and statistical pattern processing, to a wide range of application domains, from financial market analysis (“Novel Exploitation of Neural Network Methods in Financial Markets”, invited paper,World Conference on Computational Intelligence, vol. VI, pp. 3623–28, 1994) to the ‘artificial nose’ (“Novel ‘Topographic’ Nonlinear Feature Extraction using Radial Basis Functions for Concentration Coding in the ‘Artificial Nose’”,3 rd IEE International Conference on Artificial Neural Networks, pp. 95–99, Conference Publication number 372, The Institute of Electrical Engineers, 1993).
Robert Matthews is a visiting research fellow at Aston University. His research interests include probability, number theory and astronomy. His recent paper inNature (vol. 374, pp. 681–82, 1995) somehow managed to combine all three.
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Lowe, D., Matthews, R. Shakespeare vs. fletcher: A stylometric analysis by radial basis functions. Comput Hum 29, 449–461 (1995). https://doi.org/10.1007/BF01829876
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DOI: https://doi.org/10.1007/BF01829876