scholarly journals Research on the Design of Digital Signal Processing Algorithm Based on Spark Parallel Calculation

2021 ◽  
Vol 2136 (1) ◽  
pp. 012034
Author(s):  
Yifan Ming ◽  
Rui Li
Keyword(s):  
Signal Processing ◽  
Parallel Computing ◽  
Digital Signal Processing ◽  
Digital Signal ◽  
Development Trend ◽  
Point Of View ◽  
Signal Processing Algorithm ◽  
Application Performance ◽  
Time Signals ◽  
The Development Trend

Abstract Digital signal processing as a key and difficult point of network technology research and development, currently commonly used content such as LabVIEW. But from a practical point of view, while these techniques can be used to process real-time signals, they can’t handle historical offline data. The Spark parallel computing studied in this paper can be used to process offline signals. Therefore, on the basis of understanding the development trend of Spark parallel computing framework, the distributed Mallat algorithm is analyzed based on Spark parallel computing engine, and the application performance of the corresponding algorithm is verified.

An Improved Parallel FFT Algorithm Based on the GPU

2013 ◽  
Vol 647 ◽  
pp. 880-884
Author(s):  
Yong Li
Keyword(s):  
Signal Processing ◽  
Parallel Computing ◽  
Digital Signal Processing ◽  
Seismic Data ◽  
Large Scale ◽  
Digital Signal ◽  
Optimization Strategy ◽  
Parallel Fft ◽  
Parallel Fft Algorithm ◽  
Matrix Calculation

With the extensive applications of FFT in digital signal processing and image signal processing which needs a extensive application of large-scale computing, it become more and more important to improve parallelism, especially efficient and scalable parallel of FFT algorithm. This paper improves the parallelism of the FFT algorithm based on the Six-Step FFT algorithm. The introduction of GPU to parallel computing is to realize parallel FFT computing in a single machine and to improve the speed of Frontier transform. With the optimization strategy of the mapping hiding the transport matrix, the performance of parallel FFT algorithm after optimization is remarkably promoted by the assignment of matrix calculation and butterfly computation to GPU. Finally it applies to design the digital filter in seismic data.

scholarly journals Dynamic Digital Signal Processing Algorithm for Vital Signs Extraction in Continuous-Wave Radars

2021 ◽  
Vol 13 (20) ◽  
pp. 4079
Author(s):  
Carolina Gouveia ◽  
Daniel Albuquerque ◽  
José Vieira ◽  
Pedro Pinho
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Continuous Wave ◽  
Vital Signs ◽  
Digital Signal ◽  
Processing Algorithm ◽  
Signal Processing Algorithm ◽  
Radar Systems ◽  
Fitting Method ◽  
Digital Signal Processing Algorithm

Radar systems have been widely explored as a monitoring tool able to assess the subject’s vital signs remotely. However, their implementation in real application scenarios is not straightforward. Received signals encompass parasitic reflections that occur in the monitoring environment. Generally, those parasitic components, often treated as a complex DC (CDC) offsets, must be removed in order to correctly extract the bio-signals information. Fitting methods can be used, but their implementation were revealed to be challenging when bio-signals are weak or when these parasitic reflections arise from non-static targets, changing the CDC offset properties over time. In this work, we propose a dynamic digital signal processing algorithm to extract the vital signs from radar systems. This algorithm includes a novel arc fitting method to estimate the CDC offsets on the received signal. The method revealed being robust to weaker signals, presenting a success rate of 95%, irrespective of the considered monitoring conditions. Furthermore, the proposed algorithm is able to adapt to slow changes in the propagation environment.

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