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文章引入了基于提升法的自适应离散小波变换,根据LMS自适应法使伯恩斯坦预测算子自适应匹配特定的数据序列,而且应用该方法于信号的软域值去噪,数值仿真实验表明自适应提升小波变换同经典的小波变换相比,去噪后信号的信噪比效率相近,提升方法的优点在于其设计上的灵活性和计算简单。
In this paper, adaptive discrete wavelet transform based on lifting method is introduced. Based on LMS adaptive method, Bernstein predictive operator is adaptively matched to a specific data sequence. The method is applied to the denoising of soft-valued signal. The numerical simulation shows Adaptive lifting wavelet transform Compared with the classical wavelet transform, the signal-to-noise ratio of the denoised signal is similar in efficiency, and the advantage of the lifting method lies in its design flexibility and calculation simplicity.