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Integrating Matlab Neural Networks Toolbox functionality in a fully reusable software component library
Authors:Arturo J Méndez  Emilio G Roselló  María J Lado  Jacinto G Dacosta  Manuel P Cota
Affiliation:1. Department of Computer Science, Escuela Superior de Ingeniería Informática, University of Vigo, Campus As Lagoas s/n, 32004, Ourense, Spain
2. Department of Computer Science, Edificio Fundición, University of Vigo, Campus Lagoas-Marcosende, 36200, Vigo, Spain
Abstract:In this work, we present a reusable software component library, called IMO.Net Artificial Neural Networks library, which encapsulates the functionality of the Matlab Neural Networks Toolbox (MNNT). The MNNT is a powerful tool to work with neural networks. However, MNNT has not been conceived as a reusable and integrable software piece, and its results are clearly inadequate to be used for development of applications. The component library presented in this paper is fully reusable, allowing the integration of the neural networks toolbox objects and functions in software applications, independently of the platform and tools used to build it. Furthermore, this library provides two different sets of classes to the programmers, one of them presenting an application program interface (API) similar to the Matlab toolbox, and the other a fully object-oriented designed API, which is easier to use and more adequate for object-oriented and rapid application development. This library combines the advantages of being fully reusable and internally employing the MNNT to perform the algorithmic task, consequently inheriting all its power, robustness and comprehensiveness, but without its reusability limitations.
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