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[
Documents
]
lubang
DL : 0
电液伺服系统的动态递归模糊神经网络辨识与鲁棒控制研究 优秀的博士论文-Electro-hydraulic servo system dynamic recurrent fuzzy neural network identification and robust control of outstanding doctoral thesis research
Update
: 2025-04-04
Size
: 3.85mb
Publisher
:
李博
[
matlab
]
BNonlearfilter
DL : 0
给于MATLAB 环境下的非线性滤波器。此设计中用到了,混合网络建模。B样条网络和对角递归神经元网络。-In the MATLAB environment to the non-linear filter. This design used a mixed network modeling. B-spline network and on the diagonal recurrent neural network.
Update
: 2025-04-04
Size
: 8kb
Publisher
:
庞宇
[
AI-NN-PR
]
Recurrent-T-S-FNN
DL : 2
递归T-S模糊神经网络学习算法,用遗传算法优化参数-Recursive TS fuzzy neural network learning algorithm, using genetic algorithm parameters
Update
: 2025-04-04
Size
: 2kb
Publisher
:
[
AI-NN-PR
]
Fuzzy-Neural-Network-by-matlab
DL : 0
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.
Update
: 2025-04-04
Size
: 115kb
Publisher
:
林真天
[
Technology Management
]
Hybrid-training-of-recurrent-fuzzy-neural-network
DL : 0
matlab identification of cht
Update
: 2025-04-04
Size
: 33kb
Publisher
:
ramin
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