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ECG analysis in the Time-Frequency domain

2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE), 2012
The Electrocardiogram (ECG) has been established as a powerful diagnostic tool in medicine which provides important information about the patient's heart condition. The correct identification of the QRS complexes is a fundamental step in every automated or semi-automated ECG analysis method.
Neophytou, N.   +5 more
openaire   +2 more sources

Time-Domain Analysis

2001
In this chapter we have consolidated the mathematical developments necessary to relate the physical system and the differential equation describing it. This included the derivation of the impulse response, step response, and convolution integral. These quantities, which are important to the theory of filtering, were shown to be a function of the L.I ...
Roland S. Burns, Roland S. Burns
openaire   +2 more sources

Analysis of accumulated timing-jitter in the time domain

IEEE Transactions on Instrumentation and Measurement, 1998
This paper deals with the effects of accumulated timing-jitter on the signal-to-noise ratio (SNR) of real sine waves. Such a problem was recently investigated by the author, using the discrete-Fourier method. However, the frequency-domain analysis has some limitations due to the fact that some of the accumulated timing-jitter noise power, found at the ...
openaire   +1 more source

Time-Domain Analysis

2017
Heart rate variability can be analyzed by several methods, being time-domain methods the simplest measures that can be obtained from RR intervals series. Numerical indices summarizing the variability of the series are calculated from the RR intervals series. These measures are easily implemented and have low computational cost.
Constantino Antonio García Martínez   +6 more
openaire   +1 more source

Time-Frequency Domain for BCG Analysis

2018 International Conference on Computer and Applications (ICCA), 2018
The aim of this paper is to explore the time-frequency domain for the analysis of Ballistocardiogram (BCG) signals. The BCG signal reveals the mechanical activity of the heart by representing the propagated vibrations caused the ejection of blood into the arteries.
Moukadem, Ali   +5 more
openaire   +2 more sources

Time series analysis in the frequency domain

IEEE Transactions on Signal Processing, 1999
This correspondence presents a parametric frequency domain identification algorithm for autoregressive moving average (ARMA) processes that does not suffer from spectral leakage errors. It is based on an extended transfer function model that takes into account the begin and end effect of the finite data record.
Rik Pintelon, Johan Schoukens
openaire   +1 more source

Time Domain Analysis

2016
An enhanced strip theory, basically like that described in the last chapter, has been developed and used extensively over recent years for the analysis of planing boat performance and in designing planing power boats. The mechanics of this book now shifts, by both necessity and availability, from semi-analytical to more semi-numerically predicted boat ...
openaire   +2 more sources

Noise analysis for time-domain circuits

2015 IEEE International Symposium on Circuits and Systems (ISCAS), 2015
A charge integrator is an essential building block used in time-based ADCs and sensor readout circuits. In this paper, time-domain noise analysis is used to calculate the effect of all noise sources, including 1/f noise, on the voltage noise variance of the integrator.
Mehrdad A. Ghanad   +2 more
openaire   +1 more source

A RIGOROUS ANALYSIS OF TIME DOMAIN PARALLELISM∗

Parallel Algorithms and Applications, 1995
Time dependent partial differential equations are often solved using algorithms which parallelize the solution process in the spatial domain. However, as the number of processors increases, the parallel efficiency is limited by the increasing communication/computation ratio.
A. Deshpande   +3 more
openaire   +1 more source

Time series analysis in the frequency domain

IEEE Instrumentation and Measurement Technology Conference Sensing, Processing, Networking. IMTC Proceedings, 2002
This paper presents a parametric frequency domain identification algorithm for autoregressive moving average (ARMA) processes that does not suffer from spectral leakage errors. It is based on an extended transfer function model that takes into account the begin and end effect of the finite data record.
Pintelon, Rik   +2 more
openaire   +2 more sources

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