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A new model for classifying DNA code inspired by neural networks and FSA
Kang, BH and Kelarev, A and Sale, AHJ and Williams, R (2006) A new model for classifying DNA code inspired by neural networks and FSA. In: Advances in Knowledge Acquisition and Management. Lecture Notes in Computer Science (4303). Springer, Berlin, pp. 187-198.
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This paper introduces a new model of classifiers CL(V,E,l,r) designed for classifying DNA sequences and combining the flexibility of neural networks and the generality of finite state automata. Our careful and thorough verification demonstrates that the classifiers CL(V,E,l,r) are general enough and will be capable of solving all classification tasks for any given DNA dataset. We develop a minimisation algorithm for these classifiers and include several open questions which could benefit from contributions of various researchers throughout the world.
|Item Type:||Book Section|
|Journal or Publication Title:||Lecture Notes in Computer Science|
|Page Range:||pp. 187-198|
|Identification Number - DOI:||10.1007/11961239_17|
|Additional Information:||The original publication is available at www.springerlink.com|
|Date Deposited:||04 Jan 2007|
|Last Modified:||18 Nov 2014 03:12|
|Item Statistics:||View statistics for this item|
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