Title:
Fuzzy-Neural-Network-by-matlab
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Description: This 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.
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Demos
.....\rfnn_miso_scatter_demo.mdl
.....\rfnn_mimo_grid_demo.mdl
.....\rfnn_miso_scatter_demo2.mdl
.....\rfnn_miso_grid_demo.mdl
.....\rfnn_mimo_scatter_demo.mdl
.....\rfnn_miso_grid_demo3.mdl
.....\Utilities
.....\.........\SimDataGenAnfis1.m
.....\.........\MG_Check.dat
.....\.........\MG_Train.dat
.....\rfnn_miso_grid_demo2.mdl
Library
.......\RFNN_matlab.mdl
S-functions
...........\rfnn_miso_grid.m
...........\rfnn_miso_scatter.m
...........\comb.m
...........\rfnn_mimo_grid.m
...........\rfnn_mimo_scatter.m
license.txt
