An adaptive neuro-fuzzy system for efficient implementations

被引：18

作者：

Echanobe, J. ^{[1
]}

del Campo, I. ^{[1
]}

Bosque, G. ^{[1
]}

机构：

[1] Univ Basque Country, Dept Elect & Elect, Leioa 48940, Vizcaya, Spain

来源：

INFORMATION SCIENCES | 2008年 / 178卷 / 09期

关键词：

neuro-fuzzy systems; hardware implementations; embedded systems; non-linear systems;

D O I：

10.1016/j.ins.2007.12.009

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A neuro-fuzzy system specially suited for efficient implementations is presented. The system is of the same type as the well-known "adaptive network-based fuzzy inference system" (ANFIS) method. However, different restrictions are applied to the system that considerably reduce the complexity of the inference mechanism. Hence, efficient implementations can be developed. Some experiments are presented which demonstrate the good performance of the proposed system despite its restrictions. Finally, an efficient digital hardware implementation is presented for a two-input single-output neuro-fuzzy system. (c) 2007 Elsevier Inc. All rights reserved.

引用

页码：2150 / 2162

页数：13

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