The publication of the Cooley-Tukey fast Fourier transform (FFT) algorithm in 1965 has
opened a new area in digital signal processing by reducing the order of complexity of some …

Over the last decade several constructions of compactly supported wavelets originated both
from mathematical analysis and the signat processing community. The roots of critically …

Deep convolutional neural networks take GPU-days of computation to train on large data
sets. Pedestrian detection for self driving cars requires very low latency. Image recognition …

Deploying deep learning (DL) models on mobile devices draws more and more attention
recently. However, designing an efficient inference engine on devices is under the great …

This comprehensive and engaging textbook introduces the basic principles and techniques
of signal processing, from the fundamental ideas of signals and systems theory to real-world …

This book presents a coherent approach to the fast moving field of machine vision, using a
consistent notation based on a detailed understanding of the image formation process. It …

In this paper, we develop the nonsubsampled contourlet transform (NSCT) and study its
applications. The construction proposed in this paper is based on a nonsubsampled …

This article is essentially tutorial in nature. We show how any discrete wavelet transform or
two band subband filtering with finite filters can be decomposed into a finite sequence of …

The fast Fourier transform (FFT) is one of the truly great computational developments of this
century. It has changed the face of science and engineering so much so that it is not an …

Complex-valued random signals are embedded in the very fabric of science and
engineering, yet the usual assumptions made about their statistical behavior are often a …