十年来, 作为小波理论与应用的重要分支, 小波滤波得到了很大的发展, 标志着一种新的信号滤波
方法的出现. 本书是一本全面系统总结该领域研究成果和前沿进展的学术专著 …

The development of wavelet theory has in recent years spawned applications in signal
processing, in fast algorithms for integral transforms, and in image and function …

A number of fundamental results in modern statistical theory involve thresholding estimators.
This survey paper aims at reconstructing the history of how thresholding rules came to be …

In recent years, a large amount of multi-disciplinary research has been conducted on sparse
models and their applications. In statistics and machine learning, the sparsity principle is …

This book presents the state of the art in sparse and multiscale image and signal processing,
covering linear multiscale transforms, such as wavelet, ridgelet, or curvelet transforms, and …

The word 'multiscale'can mean many things. However, in this book we are generally
concerned with the representation of objects at a set of scales and then manipulating these …

We introduce a nondiagonal seismic denoising method based on the continuous wavelet
transform with hybrid block thresholding (BT). Parameters for the BT step are adaptively …

In standard wavelet methods, the empirical wavelet coefficients are thresholded term by
term, on the basis of their individual magnitudes. Information on other coefficients has no …

Wavelet analysis has been found to be a powerful tool for the nonparametric estimation of
spatially-variable objects. We discuss in detail wavelet methods in nonparametric …

We study wavelet function estimation via the approach of block thresholding and ideal
adaptation with oracle. Oracle inequalities are derived and serve as guides for the selection …