Polynomial Fourier domain as a domain of signal sparsity

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Polynomial Fourier domain as a domain of signal sparsity

— A compressive sensing (CS) reconstruction method for polynomial phase signals is proposed in this paper. It relies on the Polynomial Fourier transform, which is used to establish a relationship between the observation and sparsity domain. Polynomial phase signals are not sparse in commonly used domains such as Fourier or wavelet domain. Therefore, for polynomial phase signals standard CS algo...

متن کامل

A generalized Fourier domain: Signal processing framework and applications

In this paper, a signal processing framework in a generalized Fourier domain (GFD) is introduced. In this newly proposed domain, a parametric form of control on the periodic repetitions that occur due to sampling in the reciprocal domain is possible, without the need to increase the sampling rate. This characteristic and the connections of the generalized Fourier transform to analyticity and to...

متن کامل

Fractional Fourier domain analysis of cyclic multirate signal processing

Received December 18, 2007; accepted March 24, 2008 doi: 10.1007/s11431-008-0092-y Corresponding author (email: [email protected]) Supported partially by the National Natural Science Foundation of China (Grants Nos. 60232010 and 60572094), the National Natural Science Foundation of China for Distinguished Young Scholars (Grant No. 60625104) , as well as the Doctorship Foundation of China Educat...

متن کامل

Signal Recovery from Partial Fractional Fourier Domain Information

The problem of recovering signals from partial fractional Fourier transform information arises in wave propagation problems where the measured information is partial, spread over several observation planes, or not of sufficient spatial resolution or accuracy. This problem can be solved with the method of projections onto convex sets, with the convergence of the iterative algorithm being assured...

متن کامل

Discrete wavelet transform implementation in Fourier domain for multidimensional signal

Wavelet transforms are often calculated by using the Mallat algorithm. In this algorithm, a signal is decomposed by a cascade of filtering and downsampling operations. Computing time can be important but the filtering operations can be speeded up by using fast Fourier transform (FFT)-based convolutions. Since it is necessary to work in the Fourier domain when large filters are used, we present ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Signal Processing

سال: 2017

ISSN: 0165-1684

DOI: 10.1016/j.sigpro.2016.07.015