A hierarchical feedforward neural network model particularly suited to practical statistical pattern recognition tasks is proposed in this paper.
本文提出了一个适用于统计模式识别任务的阶层式前馈神经网络模型。
The simulation results are presented to demonstrate that the model of an unknown nonlinear dynamical system is built with the multilayered feedforward neural network model.
仿真实例进一步表明，采用神经网络建立未知非线性动态系统的在线模型具有可行性。
The model was a Feedforward Fuzzy neural network possessing five layers, and Gradient Descent was adopted as learning algorithm.
该模型采用五层前向模糊神经网络，学习算法为梯度下降法。
Then we introduce how to identify the TS model from sample data using fuzzy clustering algorithm and equivalent feedforward neural network.
然后介绍了如何使用模糊聚类算法和等价的前馈神经网络从样本数据中辨识离散的TS模型。
RBF neural network is a three-layer feedforward network and can be used to identify nonlinear model effectively.
RBF神经网络是一种三层前向网络，可有效用来进行非线性模型的辨识。
The neural network used is called DLF network, which is the combination of multilayer feedforward network with linear model.
所采用的网络为一种将线性模型与多层前向网络相结合的DLF网络。
The dynamic model of a simulator of the boiler-turbine system of a 375 MW(megawatt) thermal power plant is built by a feedforward neural network that is trained offline.
针对一个375MW热电厂的锅炉—汽轮机系统仿真模型，采用多层前向神经网络进行离线建模；
The dynamic model of a simulator of the boiler-turbine system of a 375 MW(megawatt) thermal power plant is built by a feedforward neural network that is trained offline.
针对一个375MW热电厂的锅炉—汽轮机系统仿真模型，采用多层前向神经网络进行离线建模；
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