A multiuser detection method based on adaptive wavelet network is proposed.
提出了基于自适应子波网络的多用户检测方法。
On the earning data of the tests, temperature static model of gyro has been studied by the two ways of linear regression algorithm and of wavelet network identification.
在试验数据的基础上，分别使用线性回归算法和小波网络建立了陀螺仪的静态温度模型。
Combining wavelet networks with a kind method of model structure design and parameter estimation of NARMAX model, a modified wavelet network training scheme is proposed.
将基于MGS算法的NARMAX模型结构与参数辨识的一体化算法和小波网络相结合，提出一种改进的小波网络学习算法。
The results show that this algorithm can model input and output learning kernel of dynamic nonlinear system quickly, which is superior to other learning methods of wavelet network.
结果表明该算法能够对动态非线性系统的输入输出快速学习和建模，优于其它小波网络的学习算法。
The good local amplification and multi-resolution characteristic make the wavelet network have strong adaptive capacity, fast convergence speed and high precision of prediction.
良好的局部放大特性和多分辨率学习特性使得小波神经网络比神经网络有更强的自适应能力、更快的收敛速度和更高的预报精度。
An adaptive sliding mode control based on fuzzy wavelet network is proposed to guarantee the effects of the tracking error and external disturbances can be attenuated to a specific attenuation level.
提出了一种自适应模糊小波神经网络的滑模控制策略，保证系统的跟踪误差和对外界干扰的抑制被衰减到期望的程度。
Wavelet network based nonlinear time series prediction model is submitted, and nonlinear time series prediction and its application in fault prediction are discussed in this paper.
本文提出了基于小波网络的非线性时间序列预报模型，探讨了非线性时间序列预报在故障预报中的应用。
Wavelet network based nonlinear time series prediction model is submitted, and nonlinear time series prediction and its application in fault prediction are discussed in this paper.
本文提出了基于小波网络的非线性时间序列预报模型，探讨了非线性时间序列预报在故障预报中的应用。
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