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

被引：82

作者：

Frank, T ^{[1
]}

Kraiss, KF

Kuhlen, T

机构：

[1] Siemens Business Serv, CC Machine Vis, D-53119 Bonn, Germany

[2] Aachen Univ Technol, Lehrstuhl Tech Informat, D-52074 Aachen, Germany

来源：

IEEE TRANSACTIONS ON NEURAL NETWORKS | 1998年 / 9卷 / 03期

关键词：

adaptive resonance theory; clustering; clustering analysis; neural networks; self-organization; sensor signals;

D O I：

10.1109/72.668896

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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 complement encoded input patterns, and an Euclidean ART 2A-variation. All types are tested with two-and high-dimensional input patterns in order to illustrate general capabilities and characteristics in different system environments. Based on our simulation results, Fuzzy ART seems to be less appropriate whenever input signals are corrupted by addititional noise, while ART 2A-type networks keep stable in all inspected environments. Together with other examined features, ART-architectures suited for particular applications can be selected.

引用

页码：544 / 559

页数：16

共 14 条

[1]

[Anonymous], 1990, Signal Processing, Image Processing and Patten Recognition

[2] ART 2-A - AN ADAPTIVE RESONANCE ALGORITHM FOR RAPID CATEGORY LEARNING AND RECOGNITION [J].

CARPENTER, GA ;

GROSSBERG, S ;

ROSEN, DB .

NEURAL NETWORKS, 1991, 4 (04) :493-504

[3] FUZZY ART - FAST STABLE LEARNING AND CATEGORIZATION OF ANALOG PATTERNS BY AN ADAPTIVE RESONANCE SYSTEM [J].

CARPENTER, GA ;

GROSSBERG, S ;

ROSEN, DB .

NEURAL NETWORKS, 1991, 4 (06) :759-771

[4] FUZZY ARTMAP - A NEURAL NETWORK ARCHITECTURE FOR INCREMENTAL SUPERVISED LEARNING OF ANALOG MULTIDIMENSIONAL MAPS [J].

CARPENTER, GA ;

GROSSBERG, S ;

MARKUZON, N ;

REYNOLDS, JH ;

ROSEN, DB .

IEEE TRANSACTIONS ON NEURAL NETWORKS, 1992, 3 (05) :698-713

[5] ARTMAP - SUPERVISED REAL-TIME LEARNING AND CLASSIFICATION OF NONSTATIONARY DATA BY A SELF-ORGANIZING NEURAL NETWORK [J].

CARPENTER, GA ;

GROSSBERG, S ;

REYNOLDS, JH .

NEURAL NETWORKS, 1991, 4 (05) :565-588

[6] ART-2 - SELF-ORGANIZATION OF STABLE CATEGORY RECOGNITION CODES FOR ANALOG INPUT PATTERNS [J].

CARPENTER, GA ;

GROSSBERG, S .

APPLIED OPTICS, 1987, 26 (23) :4919-4930

[7]

CARPENTER GA, 1987, IEEE COMPUTER MAR, P77

[8]

FRANK T, 1996, THESIS AACHEN U TECH

[9] FUZZY ART PROPERTIES [J].

HUANG, JX ;

GEORGIOPOULOS, M ;

HEILEMAN, GL .

NEURAL NETWORKS, 1995, 8 (02) :203-213

[10] Engineering applications of the self-organizing map [J].

Kohonen, T ;

Oja, E ;

Simula, O ;

Visa, A ;

Kangas, J .

PROCEEDINGS OF THE IEEE, 1996, 84 (10) :1358-1384

← 1 2 →