This paper presents a text categorization model based on multilayered feedforward neutral network, and introduces the design and implementation of this model.
给出一种基于多层前馈神经网络的中文文本分类模型，介绍了该模型的设计和实现。
A modified neural network structure which is composed of a linear network and a multilayered feedforward neural network (MFNN) is presented.
本文提出一种改进的神经网络结构，它由线性网络和多层前向网络两部分组成。
In this paper, a novel fast learning algorithm for multilayered feedforward neural network is introduced.
本文提出一种前馈神经网络的快速学习算法。
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。
This paper investigates the identification of unknown nonlinear dynamical system using multilayered feedforward neural network with a single hidden layer.
本文探讨了只用单个隐含层的前向神经网络对未知非线性动态系统的识别。
This paper investigates the identification of unknown nonlinear dynamical system using multilayered feedforward neural network with a single hidden layer.
本文探讨了只用单个隐含层的前向神经网络对未知非线性动态系统的识别。
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