Code covered by the BSD License  

Highlights from
Recurrent Fuzzy Neural Network (RFNN) Library for Simulink

4.0
4.0 | 2 ratings Rate this file 53 Downloads (last 30 days) File Size: 114 KB File ID: #43021 Version: 1.3
image thumbnail

Recurrent Fuzzy Neural Network (RFNN) Library for Simulink

by

 

12 Aug 2013 (Updated )

Dynamic, Recurrent Fuzzy Neural Network (RFNN) for on-line Supervised Learning.

| Watch this File

File Information
Description

This is a collection of four different S-function implementations of the recurrent fuzzy neural network (RFNN) described in detail in [1]. It is a four-layer, neuro-fuzzy network trained exclusively by error backpropagation at layers 2 and 4. The network employs 4 sets of adjustable parameters. In Layer 2: mean[i,j], sigma[i,j] and Theta[i,j] and in Layer 4: Weights w4[m,j]. The network uses considerably less adjustable parameters than ANFIS/CANFIS and therefore, its training is generally faster. This makes it ideal for on-line learning/operation. Also, its approximating/mapping power is increased due to the employment of dynamic elements within Layer 2. Scatter-type and Grid-type methods are selected for input space partitioning.
[1] C.-H. Lee, C.-C. Teng, Identification and Control of Dynamic Systems Using Recurrent Fuzzy Neural Networks, IEEE Transactions on Fuzzy Systems, vol.8, No.4, pp.349-366, Aug. 2000.

Acknowledgements

Adaptive Neuro Fuzzy Inference Systems (Anfis) Library For Simulink inspired this file.

Required Products Simulink
MATLAB
MATLAB release MATLAB 7.13 (R2011b)
MATLAB Search Path
/
/Demos
/Demos/Utilities
/Library
/S-functions
Tags for This File   Please login to tag files.
Please login to add a comment or rating.
Comments and Ratings (2)
17 Apr 2014 Mahamadou Diarra  
19 Nov 2013 Lejla BM  
Updates
23 Sep 2013 1.1

Added some details in the Description entru of this form.

24 Sep 2013 1.2

Minor corrections in the description of this submission.

08 May 2015 1.3

I have killed some redundant variables and commands. The new s-functions are more concise and therefore, easily readable. Naturally, faster execution should come as a result.

Contact us