Fuzzy-Neural-Network-by-matlab

所属分类:人工智能/神经网络/深度学习
开发工具:matlab
文件大小:115KB
下载次数:171
上传日期:2013-10-17 12:16:38
上 传 者zswseu
说明:  这是一个四个不同的S函数实现集合的递归模糊神经网络(RFNN)。该网络采用了4组可调参数,这使得它非常适合在线学习/操作,从而可应用到系统识别等方面。
(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.)

文件列表:
Demos (0, 2013-08-11)
Demos\rfnn_miso_scatter_demo.mdl (44893, 2013-08-10)
Demos\rfnn_mimo_grid_demo.mdl (55483, 2013-08-10)
Demos\rfnn_miso_scatter_demo2.mdl (37469, 2013-08-10)
Demos\rfnn_miso_grid_demo.mdl (51971, 2013-08-10)
Demos\rfnn_mimo_scatter_demo.mdl (55355, 2013-08-10)
Demos\rfnn_miso_grid_demo3.mdl (37496, 2013-08-10)
Demos\Utilities (0, 2013-08-10)
Demos\Utilities\SimDataGenAnfis1.m (593, 2013-08-10)
Demos\Utilities\MG_Check.dat (113147, 2011-03-15)
Demos\Utilities\MG_Train.dat (113147, 2011-03-15)
Demos\rfnn_miso_grid_demo2.mdl (44956, 2013-08-10)
Library (0, 2013-08-11)
Library\RFNN_matlab.mdl (45831, 2013-08-10)
S-functions (0, 2013-08-11)
S-functions\rfnn_miso_grid.m (6199, 2013-08-04)
S-functions\rfnn_miso_scatter.m (6098, 2013-08-04)
S-functions\comb.m (1148, 2013-08-10)
S-functions\rfnn_mimo_grid.m (6373, 2013-08-04)
S-functions\rfnn_mimo_scatter.m (6211, 2013-08-04)
license.txt (1315, 2013-09-24)

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