Visible to the public "Sub-sampled IFFT based compressive sampling"Conflict Detection Enabled

Title"Sub-sampled IFFT based compressive sampling"
Publication TypeConference Paper
Year of Publication2015
AuthorsLiang Zhongyin, Huang Jianjun, Huang Jingxiong
Conference NameTENCON 2015 - 2015 IEEE Region 10 Conference
Date PublishedNov. 2015
PublisherIEEE
ISBN Number978-1-4799-8641-5
Accession Number15690041
Keywordscompressed sensing, compressive measurements, compressive sampling, Discrete Fourier transforms, fast Fourier transforms, Finite impulse response filters, FIR filters, frequency domain, frequency-domain analysis, Image reconstruction, inverse transforms, Matching pursuit algorithms, one-dimensional signal, pubcrawl170104, random filter, random filter-based method, random-tap FIR filter, SSIFFT, sub-sampled IFFT, sub-sampled IFFT-based compressive sampling, sub-sampled inverse fast Fourier transform, time domain, Time measurement, time-domain analysis, two-dimensional signal
Abstract

In this paper, a new approach based on Sub-sampled Inverse Fast Fourier Transform (SSIFFT) for efficiently acquiring compressive measurements is proposed, which is motivated by random filter based method and sub-sampled FFT. In our approach, to start with, we multiply the FFT of input signal and that of random-tap FIR filter in frequency domain and then utilize SSIFFT to obtain compressive measurements in the time domain. It requires less data storage and computation than the existing methods based on random filter. Moreover, it is suitable for both one-dimensional and two-dimensional signals. Experimental results show that the proposed approach is effective and efficient.

URLhttps://ieeexplore.ieee.org/document/7373066
DOI10.1109/TENCON.2015.7373066
Citation Key7373066