For access to this article, please select a purchase option:
Buy conference paper PDF
Buy Knowledge Pack
IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.
Smoothed Pseudo Wigner-Ville Distribution (SPWVD) is a common and effective time-frequency analysis algorithm which is widely used in signal processing. It’s improved from Wigner-Ville Distribution (WVD) by adding a window function both in the time domain and frequency domain which can effectively suppress cross-terms. However, it also enlarges the work remarkably. As a result, the application of SPWVD is greatly restricted. This paper proposed a parallel implementation of SPWVD based on Compute Unified Device Architecture (CUDA) which runs on GPU. By combining reduction operation and shared memory, we design a parallel summation method which can save a lot of time effectively. Numerical experiments are also provided to demonstrate that the proposed method is more efficient especially when the amount of data increases.