scholarly journals DIGITAL PROCESSING OF INVESTIGATED DAC’S SIGNALS

2010 ◽  
Vol 2 (1) ◽  
pp. 45-49
Author(s):  
Tomas Ustinavičius
Keyword(s):  
Signal Processing ◽  
Digital Filters ◽  
Internal Noise ◽  
Digital Signal ◽  
Digital Processing ◽  
Periodic Sequence ◽  
Comb Filter ◽  
The Given ◽  
Very High

The article shows that in designed algorithm for determination of digital signal processing and settling time of DAC the greatest influence on the test has 1/f type internal noise of the sampling converter. It is offered to filter the preliminary digital signal and to construct pseudo-periodic sequence from n realization periods of examined signals and internal noise. It is shown, that standard digital filters because of very high the demands are not suitable. The structure of digital comb filter is proposed. Investigations have shown that the given filter can effectively be used for filtering of various signals.

Study on Auto-Search Algorithm Based on Subsection Correlation for Loran-C

2012 ◽  
Vol 241-244 ◽  
pp. 1751-1755
Author(s):  
Yin Bing Zhu ◽  
Ke Jing Cao ◽  
Bao Li
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Arrival Time ◽  
Search Algorithm ◽  
Digital Signal ◽  
Digital Processing ◽  
Digital Receiver ◽  
Maximum Correlation ◽  
Key Steps ◽  
Signal Search

Auto-search is one of the key steps in digital signal processing for Loran-C receivers, however, for digital sampling Loran-C signal, the principle search algorithm is unable to realize signal search veraciously because of the asynchronism between sampling clock and transmitting station clock. For this question, an auto-search algorithm based on subsection correlation for Loran-C is presented after analyzing the principle search algorithm. The experiment results show that for the received digital Loran-C signal, there are several correlation and accumulation values of master and secondary stations to exceed the search thresholds; the maximum correlation and accumulation value of the presented algorithm is far higher than that of the principle algorithm. That is to say, the presented algorithm can search the arrival time of master and secondary station successfully, solve the problem of clock asynchronism effectively, and enhance the search sensitivity of the receiver, which have great significance for digital processing of Loran-C signal and the engineering realization of Loran-C digital receiver.

scholarly journals Eliminating unwanted signals in sound by using digital signal processing system

2020 ◽  
Vol 18 (2) ◽  
pp. 829
Author(s):  
Amer T Saeed ◽  
Zaid Raad Saber ◽  
Ahmed M. Sana ◽  
Musa A. Hameed
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Digital Filters ◽  
Processing System ◽  
Digital Signal ◽  
Noise Signal ◽  
Time Range ◽  
Signal Processing System ◽  
Digital Signal Processing System ◽  
Sound Files

<p><a name="_Hlk536186602"></a><span style="font-size: 9pt; font-family: 'Times New Roman', serif;">Unwanted signals or noise signals in sound files are considered one of the major challenges and issues for a thousand users. It is impossible to reduce or remove these noise signals without identifying their types and ranges. Therefore, to address one of the big problems in the digital or analogue communication, which is noise signals or unwanted signals, an adaptive selection method and noise signal removal algorithm are proposed in this research. The proposed algorithm is done through specifying the types of undesirable signals, frequency, and time range, then utilizing digital signal processing system which includes design several types of digital filters based on the types and numbers of unwanted signals. Four digital filters are used in this research to remove noise signals from the sound file by implementing the proposed algorithm using Matlab Code. Results show that our proposed algorithm was done successfully and the whole noise signals were removed without any negative consequence in the output sound signal. </span><span style="font-family: 'Times New Roman', serif; font-size: 9pt;">Unwanted signals or noise signals in sound files are considered one of the major challenges and issues for a thousand users. It is impossible to reduce or remove these noise signals without identifying their types and ranges. Therefore, to address one of the big problems in the digital or analogue communication, which is noise signals or unwanted signals, an adaptive selection method and noise signal removal algorithm are proposed in this research. The proposed algorithm is done through specifying the types of undesirable signals, frequency, and time range, then utilizing digital signal processing system which includes design several types of digital filters based on the types and numbers of unwanted signals. Four digital filters are used in this research to remove noise signals from the sound file by implementing the proposed algorithm using Matlab Code. Results show that our proposed algorithm was done successfully and the whole noise signals were removed without any negative consequence in the output sound signal.</span></p>

scholarly journals Spatial-Temporal Signals and Clinical Indices in Electrocardiographic Imaging (II): Electrogram Clustering and T-Wave Alternans

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3070 ◽  
Author(s):  
Raúl Caulier-Cisterna ◽  
Manuel Blanco-Velasco ◽  
Rebeca Goya-Esteban ◽  
Sergio Muñoz-Romero ◽  
Margarita Sanromán-Junquera ◽  
...  
Keyword(s):  
Signal Processing ◽  
Cardiac Electrophysiology ◽  
Current Knowledge ◽  
Maximum Amplitude ◽  
Digital Signal ◽  
Digital Processing ◽  
Temporal Analysis ◽  
Electrocardiographic Imaging ◽  
T Wave ◽  
T Wave Alternans

During the last years, attention and controversy have been present for the first commercially available equipment being used in Electrocardiographic Imaging (ECGI), a new cardiac diagnostic tool which opens up a new field of diagnostic possibilities. Previous knowledge and criteria of cardiologists using intracardiac Electrograms (EGM) should be revisited from the newly available spatial–temporal potentials, and digital signal processing should be readapted to this new data structure. Aiming to contribute to the usefulness of ECGI recordings in the current knowledge and methods of cardiac electrophysiology, we previously presented two results: First, spatial consistency can be observed even for very basic cardiac signal processing stages (such as baseline wander and low-pass filtering); second, useful bipolar EGMs can be obtained by a digital processing operator searching for the maximum amplitude and including a time delay. In addition, this work aims to demonstrate the functionality of ECGI for cardiac electrophysiology from a twofold view, namely, through the analysis of the EGM waveforms, and by studying the ventricular repolarization properties. The former is scrutinized in terms of the clustering properties of the unipolar an bipolar EGM waveforms, in control and myocardial infarction subjects, and the latter is analyzed using the properties of T-wave alternans (TWA) in control and in Long-QT syndrome (LQTS) example subjects. Clustered regions of the EGMs were spatially consistent and congruent with the presence of infarcted tissue in unipolar EGMs, and bipolar EGMs with adequate signal processing operators hold this consistency and yielded a larger, yet moderate, number of spatial–temporal regions. TWA was not present in control compared with an LQTS subject in terms of the estimated alternans amplitude from the unipolar EGMs, however, higher spatial–temporal variation was present in LQTS torso and epicardium measurements, which was consistent through three different methods of alternans estimation. We conclude that spatial–temporal analysis of EGMs in ECGI will pave the way towards enhanced usefulness in the clinical practice, so that atomic signal processing approach should be conveniently revisited to be able to deal with the great amount of information that ECGI conveys for the clinician.

Time Determination of BGO-APD Detectors by Digital Signal Processing for Positron Emission Tomography

2009 ◽  
Vol 56 (5) ◽  
pp. 2600-2606 ◽  
Author(s):  
Jean-Daniel Leroux ◽  
Jean-Pierre Martin ◽  
Daniel Rouleau ◽  
Catherine M. Pepin ◽  
Jules Cadorette ◽  
...  
Keyword(s):  
Positron Emission Tomography ◽  
Signal Processing ◽  
Digital Signal Processing ◽  
Digital Signal ◽  
Emission Tomography ◽  
Positron Emission ◽  
Time Determination

scholarly journals A Method of Increasing Digital Filter Performance Based on Truncated Multiply-Accumulate Units

2020 ◽  
Vol 10 (24) ◽  
pp. 9052
Author(s):  
Pavel Lyakhov ◽  
Maria Valueva ◽  
Georgii Valuev ◽  
Nikolai Nagornov
Keyword(s):  
Signal Processing ◽  
Theoretical Analysis ◽  
Digital Signal Processing ◽  
Digital Filter ◽  
Digital Filters ◽  
Digital Signal ◽  
Digital Filtering ◽  
Filter Performance ◽  
Filter Architecture ◽  
Hardware Costs

This paper proposes new digital filter architecture based on a modified multiply-accumulate (MAC) unit architecture called truncated MAC (TMAC), with the aim of increasing the performance of digital filtering. This paper provides a theoretical analysis of the proposed TMAC units and their hardware simulation. Theoretical analysis demonstrated that replacing conventional MAC units with modified TMAC units, as the basis for the implementation of digital filters, can theoretically reduce the filtering time by 29.86%. Hardware simulation showed that TMAC units increased the performance of digital filters by up to 10.89% compared to digital filters using conventional MAC units, but were associated with increased hardware costs. The results of this research can be used in the theory of digital signal processing to solve practical problems such as noise reduction, amplification and suppression of the frequency spectrum, interpolation, decimation, equalization and many others.

EDUCATIONAL PLATFORM FOR REAL-TIME DIGITAL SIGNAL PROCESSING: PRACTICAL APPLICATIONS OF DIGITAL FILTERS

2017 ◽  
Vol 36 (1) ◽  
Author(s):  
Wesley Becari ◽  
Rodrigo B. dos Santos ◽  
André B. Carlos ◽  
Rafael A. Biliatto ◽  
Henrique E. M. Peres
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Real Time ◽  
Digital Filters ◽  
Digital Signal ◽  
Practical Applications

FIR Digital Filter Design Based on Virtual Instrument

2013 ◽  
Vol 684 ◽  
pp. 653-656
Author(s):  
Yu Jian Du ◽  
Zu Bin Chen ◽  
Teng Yu ◽  
Yang Yang
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Virtual Instrument ◽  
Digital Filters ◽  
Filter Design ◽  
Digital Signal ◽  
Seismic Signal ◽  
Digital Filter Design ◽  
Digital World ◽  
Fir Digital Filters

With the information era and the advent of the digital world, digital signal processing has become extremely important in today's one of the disciplines and technical fields.Digital signal processing in seismic signal ,communications, voice, image, automatic control radar, and other fields has been widely used.In this paper,I design several kind of FIR digital filters based on virtual instrument to solve the problem that signal noise reduction.

scholarly journals A VLSI DSP DESIGN AND IMPLEMENTATION OF COMB FILTER USING UN-FOLDING METHODOLOGY

2012 ◽  
pp. 72-77
Author(s):  
PURU GUPTA ◽  
TARUN KUMAR RAWAT
Keyword(s):  
Signal Processing ◽  
Computation Time ◽  
Digital Signal ◽  
Vlsi Circuits ◽  
Comb Filter ◽  
Destructive Interference ◽  
Sample Period ◽  
Iteration Bound ◽  
Comb Filters ◽  
Digital Waveguide

In signal processing, a comb filter adds a delayed version of a signal to itself, causing constructive and destructive interference. Comb filters are used in a variety of signal processing applications that is Cascaded Integrator-Comb filters, Audio effects, including echo, flanging, and digital waveguide synthesis and various other applications. Comb filter when implemented has lower through-put as the sample period can not be achieved equal to the iteration bound because node computation time of comb filter is larger than the iteration bound. Hence throughput remains less. This paper present the comb filter using one of the methodology needed to design custom or semi custom VLSI circuits named as Un-Folding which increases the throughput of the comb filter. Un-Folding is a transformation technique that can be applied to a DSP program to create a new program describing more than one iteration of the original program. It can unravel hidden con-currency in digital signal processing systems described by DFGs. Therefore, unfolding has been used for the sample period reduction of the comb filter for its higher throughput.

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