Comparative analysis of fuzzy ART and ART-2A network clustering performance

Comparative Analysis of Fuzzy ART and ART-2A Network Clustering Performance - Neural Networks, IEEE Transactions on

Adaptive resonance theory (ART) describes a family of self-organizing neural networks, capable of clustering arbitrary sequences of input patterns into stable recognition codes. Many different types of ART-networks have been developed to improve clustering capabilities. In this paper we compare clustering performance of different types of ART-networks: Fuzzy ART, ART 2A with and without complem...

A Comparative Analysis of Fuzzy ART Neural Network Implementations: The Advantages of Reconfigurable Computing

This paper analyzes the performance differences found between software and hardware/sofware implementations of a reformulated Fuzzy ART neural network algorithm. This reformulated algorithm is a solution for a real time radar signal clustering problem. The software implementations run on a 50MHz TMS320C40 DSP, and the hardware/sofware implementation runs on the same DSP for its software part, w...

Performance Art/Life Art/ Mediafication

ART-based fuzzy classifiers: ART fuzzy networks for automatic classification

Performance of Fuzzy ART neural network and hierarchical clustering for part–machine grouping based on operation sequences

The problem context for this study is one of identifying families of parts having a similar sequence of operations. This is a prerequisite for the implementation of cellular manufacturing, group technology, just-in-time manufacturing systems and for streamlining material flows in general. Given this problem context, this study develops an experimental procedure to compare the performance of a f...