Browse Publications Technical Papers 2004-01-0294
2004-03-08

Adaptive Fuzzy Neural Networks With Global Clustering 2004-01-0294

This paper proposes a novel algorithm. This algorithm is called Self-Organizing Fuzzy Neural Network (SOFNN). SOFNN revolutionizes how researchers apply control theories, image/signal processing on control systems and other applications. In general, SOFNN is an identification technique that automatically initiates, builds and fine-tunes the required network parameters. SOFNN evaluates required structures without predefined parameters or expressions regarding systems. SOFNN sets out to learn and configure a system's characteristics. Self-constructing and self-tuning features enable SOFNN to handle complex, non-linear, and time-varying systems with higher accuracy, making systems identification easier. SOFNN constructs and fine-tunes the system parameter through two phases. The two phases are the construction and the parameter-tuning phase. The two phases run concurrently allowing SOFNN to identify systems on-line. Because of the self-construction feature, SOFNN has global clustering feature. The global clustering feature means the network is capable of covering every possible incident of the variables universe of discourse. Simulation results confirm the ability of SOFNN to capture both complexity and ambiguity.

SAE MOBILUS

Subscribers can view annotate, and download all of SAE's content. Learn More »

Access SAE MOBILUS »

Members save up to 18% off list price.
Login to see discount.
Special Offer: Download multiple Technical Papers each year? TechSelect is a cost-effective subscription option to select and download 12-100 full-text Technical Papers per year. Find more information here.
We also recommend:
TECHNICAL PAPER

4 Stroke Gasoline Engine Performance Optimization Using Statistical Techniques

2001-01-1800

View Details

TECHNICAL PAPER

Validation of a Parametric Vehicle Modelling Tool Using Published Data for Prototype and Production Vehicles with Advanced Powertrain Technologies

2005-01-3481

View Details

Book
BOOK

JATCO Technical Review No. 11

View Details

X