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STFLWARP20L PDF预览

STFLWARP20L

更新时间: 2024-09-30 22:05:47
品牌 Logo 应用领域
意法半导体 - STMICROELECTRONICS /
页数 文件大小 规格书
4页 92K
描述
ADAPTIVE FUZZY MODELLER

STFLWARP20L 数据手册

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AFM 1.0  
ADAPTIVE FUZZY MODELLER  
ADVANCED DATA  
Up to 8 Input Variables and 4 Output Variables  
Up to 8 Fuzzy Sets for each Input Variables  
Up to 214 Fuzzy Rules  
DESCRIPTION  
Adaptive Fuzzy Modeller (AFM) is a tool that easily  
allows to obtain a model of a system based on  
Fuzzy Logic data structure, starting from the sam-  
pling of a process/function expressed in terms of  
Input\Output values pairs (patterns).  
Rules Learning Phase using an unsupervised  
WTA-FAM  
Membership Functions Learning Phase using  
a supervised BACK-FAM  
Its primary capability is the automatic generation of  
a database containing the inference rules and the  
parameters describing the membership functions.  
The generated Fuzzy Logic knowledge base rep-  
resents an optimized approximation of the proc-  
ess/function provided as input.  
Automatic and Manual Learning Rate  
Rules Minimizer  
Gaussian and Triangular Membership  
Functions Shape  
The AFM has the capability to translate its project  
files to FUZZYSTUDIO project files, MATLAB  
and C code, in order to use this environment as a  
support for simulation and control .  
Inference method based on Product or Minimum  
Step-by-Step and from File Simulation available  
The block diagram in fig.2 illustrates the AFM logic  
flow.  
Supported Target: W.A.R.P. 1.1, W.A.R.P. 2.0,  
MATLAB and ANSI C  
Figure 1. Block Diagram  
May 1996  
1/4  
This is advance information on a new product now in development or undergoing evaluation. Details are subject to change without notice.  

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