An Object-Oriented Toolbox for Adaptive Neural Networks' Implementation

Abstract

Neural Networks are massively parallel processing systems, that require expensive and usually not available hardware, in order to be realized. Fortunately, the development of effective and accessible software, makes their simulation easy. Thus, various neural network's implementation tools exist in the market, which are oriented to the specific learning algorithm used. Furthermore, they can simulate only fixed size networks. In this work, we present some object-oriented techniques that have been used to defined some types of neuron and network objects, that can be used to realize, in a localized approach, some fast and powerful learning algorithms which combine results of the optimal filtering and the multi-model partitioning theory. Thus, one can build and implement intelligent learning algorithms that face both, the training as well as the on-line adjustment of the network size. Furthermore, the design methodology used, results to a system modeled as a collection of concurrent executable objects, making easy the parallel implementation. The whole design results in a general purpose tool box which is characterized by maintainability, reusability, and increased modularity. The provided features are shown by the presentation of some practical applications.

Automization of Object Oriented Design Using Back Propagation Neural Network for Better Maintainability of Software

“…A lot of time is needed to maintain the existing software to analyse and comprehend the available source code [3]. Some tools are available to support Class Responsibility Assignment (CRA) which can be used for analysing and designing OOP, was designed to provide a cognitive toolkit for designers and developers [4]. Designing the object-oriented software (OOS) is the complex process and in the initial steps it's included analysing the class candidates and allocating responsibilities of a system to them [5].…”

Ευφυή Υβριδικά Συστήματα Με Τμηματοποίηση

“…Χρειάζεται βελτιώσεις όσον αφορά τη διεπιφάνεια χρήστη που πρέπει να γίνει πιο φιλική με την υλοποίηση παραθυρικού μοντέλου επικοινωνίας με το χρήστη (όπως π.χ. στο εργαλείο που περιγράφεται στην εργασία (Manioudakis & Likothanassis 2001 )).…”