Deep learning is transforming most areas of science and technology, including electron
microscopy. This review paper offers a practical perspective aimed at developers with …

FFT methods have become a fundamental tool in computational micromechanics since they
were first proposed in 1994 by Moulinec and Suquet for the homogenization of composites …

This article is aimed to study the modeling problems of combinational signals or periodic
signals. To overcome the computation complexity of modeling the signals with plenty of …

Analysis and processing of very large data sets, or big data, poses a significant challenge.
Massive data sets are collected and studied in numerous domains, from engineering …

With the development and popularization of computer network technology, the copyright
protection of stereo images is a serious problem to be solved. Based on ternary number …

Considerable interest has been devoted to converting mechanical energy into electricity
using polymer nanofibres. In particular, piezoelectric nanofibres produced by …

FFTW is an implementation of the discrete Fourier transform (DFT) that adapts to the
hardware in order to maximize performance. This paper shows that such an approach can …

We propose a novel approach to learn and recognize natural scene categories. Unlike
previous work, it does not require experts to annotate the training set. We represent the …

FFT literature has been mostly concerned with minimizing the number of floating-point
operations performed by an algorithm. Unfortunately, on present-day microprocessors this …

This book presents a broad overview of numerical methods for students and professionals in
computationally oriented disciplines who need to solve mathematical problems. It differs …