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Multi-layered nonlinear neural network is now an effective technology for gas chimney research. “多层非线性神经网络技术”是目前研究气烟囱比较有效的方法。
nonlinear neural network 非线性神经网络
Nonlinear ANC Based on RBF Neural Networks? 基于径向基神经网络的非线性自适应除噪
The theory of fuzzy neural network (FNN) modeling for nonlinear systems is presented. 摘要论述了模糊系统和神经网络相结合的非线性系统辨识理论。
Neural Network Trace Editor Training. 神经网络道编辑训练。
The BP network reflects the nonlinear static gain. The linear neural network reflects the linear dynamic subsystem. 其中;bp网络反映了非线性静态增益;线性神经网络反映了线性动态子系统.
Neural network(NN)can be trained as a predistorter which linearlizes nonlinear power amplifier with memory. 该方法在收敛速度和精度上都有明显提高。
A fuzzy neural network (FNN) control scheme for a class of complicated nonlinear systems was presented. 针对一类复杂非线性系统，提出一种模糊神经网络(FNN)控制方案。
After that, an FDD approach based on a double neural network for slow time-varying nonlinear system is proposed. 根据不同的动力系统参数存在的时变特点，提出了基于在线学习的时变非线性系统双重神经网络故障检测方法。
On solving this category issue, neural network has very strong capability to handle a large scale and complicated nonlinear dynamics system. 在解决这类问题方面，神经网络具有很强的处理大规模复杂非线性动力学系统的能力。
The neural network can preferably solve the non-linear problem. 利用神经网络建模可以较好地解决非线性问题。
As a new type of recurrent neural network,echo state network(ESN) is applied to nonlinear system identification and chaotic time series prediction. ESN(回声状态网络)是一种新型的递归神经网络;可有效处理非线性系统辨识以及混沌时间序列预测问题.
Wavelet-based and neural network papers from the Journal Network! 详细说明:基于小波和神经网络的论文,来自期刊网!
The Research on the Chaotic Neural Network Encoding? 混沌神经网络编码研究?
Convergent rate of certain neural network models s. N. 一类神经网络模型的平衡点的收敛速率。
Neural Network Inverse Control of Two-motor Synchronous System P. 中国科学技术大学中国科学技术大学两电机同步系统的神经网络逆控制。
And carry out a neural network deign and simulation with MATLAB. 并用MATLAB仿真的方法进行神经网络的设计和模拟。
Martin Hagan, Howard Demuth and Mark Beale. Neural Network Design. 戴葵等译.;神经网络设计
Neural Networks Horizon Picker Training. 神经网络层位拾取训练。
We use neural network because of its simpleness and accurateness. 使用神经网络来进行客户离网预警的优点在于其模型建立简单，识别精度高。