SIG—A general-purpose signal processing program

1987 ◽  
Vol 75 (9) ◽  
pp. 1322-1332 ◽  
Author(s):  
D.L. Lager ◽  
S.G. Azevedo
2011 ◽  
Vol 28 (1) ◽  
pp. 1-14 ◽  
Author(s):  
W. van Straten ◽  
M. Bailes

Abstractdspsr is a high-performance, open-source, object-oriented, digital signal processing software library and application suite for use in radio pulsar astronomy. Written primarily in C++, the library implements an extensive range of modular algorithms that can optionally exploit both multiple-core processors and general-purpose graphics processing units. After over a decade of research and development, dspsr is now stable and in widespread use in the community. This paper presents a detailed description of its functionality, justification of major design decisions, analysis of phase-coherent dispersion removal algorithms, and demonstration of performance on some contemporary microprocessor architectures.


Author(s):  
Dimitris Arabadjis ◽  
Michael Exarhos ◽  
Fotios Giannopoulos ◽  
Solomon Zannos ◽  
Panayiotis Rousopoulos ◽  
...  

In this chapter the authors outline some research works characteristic for the application of Signal Processing and Pattern Analysis techniques to the automatic reconstruction / reassembly of fragmented archaeological objects. The studies described in the chapter cover in their application cases a variety of archaeological objects, ranging from documents and wall-paintings to pots and sculptures. Moreover there are distinct approaches in the treatment of these application cases, with some works focusing on the development of a reconstruction methodology of general purpose, while others aim to develop a complete system to treat a specific application problem. The methodologies developed in these studies are outlined in the chapter so as to retain the basic technical elements of each approach that compile the proposed reconstruction algorithmic scheme.


Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4137
Author(s):  
Vilém Kledrowetz ◽  
Lukáš Fujcik ◽  
Roman Prokop ◽  
Jiří Háze

In this paper, a second-order asynchronous delta-sigma modulator (ADSM) is proposed based on the active-RCintegrators. The ADSM is implemented in the 0.18 μ m CMOS Logic or Mixed-Signal/RF, General Purpose process from the Taiwan Semiconductor Manufacturing Company with a center frequency of 848 kHz at a supply voltage of 1 V with a 92 dB peak signal-to-noise and distortion ratio ( S N D R ), which corresponds to 15 bit resolution. These parameters were achieved in all the endogenous bioelectric signals bandwidth of 10 kHz. The ADSM dissipated 295 μ W and had an area of 0.54 mm 2 . The proposed ADSM with a high resolution, wide bandwidth, and rail-to-rail input voltage range provides the universal solution for endogenous bioelectric signal processing.


2001 ◽  
Vol 18 (1) ◽  
pp. 105-113 ◽  
Author(s):  
Jon F. Bell ◽  
Peter J. Hall ◽  
Warwick E. Wilson ◽  
Robert J. Sault ◽  
Rick J. Smegal ◽  
...  

AbstractDigital signal processing is one of many valuable tools for suppressing unwanted signals or inter-ference. Building hardware processing engines seems to be the way to best implement some classes of interference suppression but is, unfortunately, expensive and time-consuming, especially if several miti-gation techniques need to be compared. Simulations can be useful, but are not a substitute for real data. CSIRO’s Australia Telescope National Facility has recently commenced a ‘software radio telescope’ project designed to fill the gap between dedicated hardware processors and pure simulation. In this approach, real telescope data are recorded coherently, then processed offline. This paper summarises the current contents of a freely available database of base band recorded data that can be used to experiment with signal processing solutions. It includes data from the following systems: single dish, multi-feed receiver; single dish with reference antenna; and an array of six 22 m antennas with and without a reference antenna. Astronomical sources such as OH masers, pulsars and continuum sources subject to interfering signals were recorded. The interfering signals include signals from the US Global Positioning System (GPS) and its Russian equivalent (GLONASS), television, microwave links, a low-Earth-orbit satellite, various other transmitters, and signals leaking from local telescope systems with fast clocks. The data are available on compact disk, allowing use in general purpose computers or as input to laboratory hardware prototypes.


1997 ◽  
Vol 68 (1) ◽  
pp. 951-954 ◽  
Author(s):  
A. Murari ◽  
P. Martin ◽  
O. Hemming ◽  
G. Manduchi ◽  
L. Marrelli ◽  
...  

Author(s):  
Vladimir D. Orlic ◽  
Miroslav Peric ◽  
Predrag Milicevic ◽  
Zoran Banjac ◽  
Sasa Milicevic

2019 ◽  
Vol 10 (2) ◽  
pp. 143-150
Author(s):  
Rafał KRUK ◽  
Zbigniew REMPAŁA

The paper presents a discussion on the issue of possible acceleration of radiolocation signal processing algorithms in seekers using graphics processing units. A concept and implementation examples of algorithms performing digital data filtering on general purpose central and graphics processing units are introduced. The results of performance comparison of central and graphics processing units during computing discrete convolution are presented at the end of the paper.


2013 ◽  
Vol 48 (2) ◽  
pp. 51-61 ◽  
Author(s):  
Petr Roule ◽  
Ondřej Jakubov ◽  
Pavel Kovář ◽  
Petr Kařmařík ◽  
František Vejražka

ABSTRACT Signal processing of the global navigation satellite systems (GNSS) is a computationally demanding task due to the wide bandwidth of the signals and their complicated modulation schemes. The classical GNSS receivers therefore utilize tailored digital signal processors (DSP) not being flexible in nature. Fortunately, the up-to-date parallel processors or graphical processing units (GPUs) dispose sufficient computational power for processing of not only relatively narrow band GPS L1 C/A signal but also the modernized GPS, GLONASS, Galileo and COMPASS signals. The performance improvement of the modern processors is based on the constantly increasing number of cores. This trend is evident not only from the development of the central processing units (CPUs), but also from the development of GPUs that are nowadays equipped with up to several hundreds of cores optimized for video signals. GPUs include special vector instructions that support implementation of massive parallelism. The new GPUs, named as general-purpose computation on graphics processing units (GPGPU), are able to process both graphic and general data, thus making the GNSS signal processing possible. Application programming interfaces (APIs) supporting GPU parallel processing have been developed and standardized. The most general one, Open Computing Language (Open CL), is now supported by most of the GPU vendors. Next, Compute Unified Device Architecture (CUDA) language was developed for NVidia graphic cards. The CUDA language features optimized signal processing libraries including efficient implementation of the fast Fourier transform (FFT). In this paper, we study the applicability of the GPU approach in GNSS signal acquisition. Two common parallel DSP methods, parallel code space search (PCSS) and double-block zero padding (DBZP), have been investigated. Implementations in the C language for CPU and the CUDA language for GPU are discussed and compared with respect to the acquisition time. It is shown that for signals with long ranging codes (with 10230 number of chips - Galileo E5, GPS L5 etc.). Paper presented at the "European Navigation Conference 2012", held in Gdansk, Poland


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