ganf is a class of nonlinear adaptive filter achieved by replacing the boolean function operator with a neural operator.
ganf是用神经运算器代替级叠滤波器中的布尔运算器后得到的一类非线性自适应神经滤波器。
main contents studied include: (1) nonlinear adaptive filter predicting chaotic time series and hopping frequency code;
主要内容为:(1)非线性自适应滤波器对混沌时间序列及跳频码的预测;
based on the deterministic and nonlinear characterization of the chaotic signals, a new reduced parameter nonlinear adaptive filter is proposed to make adaptive predictions of chaotic time series.
基于混沌动力系统的相空间延迟坐标重构,利用混沌序列固有的确定性和非线性,提出了用于混沌时间序列预测的一种少参数非线性自适应滤波预测模型。