Selforganizing Cliiord Neural Network

A new Selforganizing Neural Network using Cli ord Algebra

This paper presents a novel selforganizing type RBF neural network. The design was done using the Cliiord algebra or geometric algebra. Real valued neural nets for function approximation require feature enhancement, dilatation and rotation operations and are limited by the Euclidean metric. This operations can be carried out more eeciently if the network structures are designed in the Cliiord a...

Geometric Neural Networks

The representation of the external world in biological creatures appears to be deened in terms of geometry. This suggests that researchers should look for suitable mathematical systems with powerful geometric and algebraic characteristics. In such mathematical context the design and implementation of neural networks will be certainly more advantageous. This paper presents the generalization of ...

Selforganizing Clifford Neural Networks

Selforganizing Classification on the Reuters News Corpus

In this paper we propose an integration of a selforganizing map and semantic networks from WordNet for a text classification task using the new Reuters news corpus. This neural model is based on significance vectors and benefits from the presentation of document clusters. The Hypernym relation in WordNet supplements the neural model in classification. We also analyse the relationships of news h...

Solar and Its Hardware Development

The focus of this paper is a novel parallel and selforganizing neural network hardware architecture and its development. This architecture is based on self-organizing learning array (SOLAR) algorithm reported earlier. This hardware architecture is aimed at hundreds of tradit ional reconfigurable field programmable gate arrays (FPGAs). Its reconfigurability scheme is distinct from the usual appr...