Results 241 to 250 of about 590,374 (288)

Heart Rate Signal Decomposition

Methods of Information in Medicine, 2000
Abstract:This paper proposes a method for decomposing heart rate fluctuations into background, respiratory and blood pressure oriented fluctuations. A signal cancellation scheme using the adaptive RLS algorithm has been introduced for canceling respiration and blood pressure oriented changes in the heart rate fluctuations.
H, Mizuta, K, Yana
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Composite signal decomposition

IEEE Transactions on Audio and Electroacoustics, 1970
A technique for decomposing a composite signal, which consists of the superposition of known multiple signals overlapping in time, is described. Decomposition includes determining the number of signals present, their epochs (arrival times), and amplitudes. The procedure is investigated for the noise-free and noisy situation.
D. Childers, R. Varga, N. Perry
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A NOVEL SIGNAL DECOMPOSITION APPROACH — ADAPTIVE FOURIER DECOMPOSITION

Advances in Adaptive Data Analysis, 2011
This paper presents a novel signal decomposition approach — adaptive Fourier decomposition (AFD), which decomposes a given signal based on its physical characters. The algorithm is described in detail, that is based on recent theoretical studies on analytic instantaneous frequencies and stands as a realizable variation of the greedy algorithm.
Zhang, Liming, Li, Hong
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Decomposition of multiunit electromyographic signals

IEEE Transactions on Biomedical Engineering, 1999
We have developed a comprehensive technique to identify single motor unit (SMU) potentials and to decompose overlapped electromyographic (EMG) signals into their constituent SMU potentials. This technique is based on one-channel EMG recordings and is easily implemented for many clinical EMG tests. There are several distinct features of our technique: 1)
J, Fang, G C, Agarwal, B T, Shahani
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Decomposition of Surface EMG Signals

Journal of Neurophysiology, 2006
This report describes an early version of a technique for decomposing surface electromyographic (sEMG) signals into the constituent motor unit (MU) action potential trains. A surface sensor array is used to collect four channels of differentially amplified EMG signals. The decomposition is achieved by a set of algorithms that uses a specially developed
Carlo J, De Luca, Alexander, Adam, Robert, Wotiz, L Donald, Gilmore, S Hamid, Nawab   +4 more
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Decomposition of mechanical signals

2009 35th Annual Conference of IEEE Industrial Electronics, 2009
Time frequency transformations have gained increasing attention for the characterization of non-stationary signals in a broad spectrum of science and engineering applications. Signals encountered in rotary machine systems can be broadly classified as being either stationary or nonstationary.
Cao Jun, Wang Xingsong
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Weighted sparse signal decomposition

2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012
Standard sparse decomposition (with applications in many different areas including compressive sampling) amounts to finding the minimum l0-norm solution of an underdetermined system of linear equations. In this decomposition, all atoms are treated ‘uniformly’ for being included or not in the decomposition.
Massoud Babaie-Zadeh, Behzad Mehrdad, Georgios B. Giannakis   +2 more
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Signal-Adaptive Decomposition of Multicomponent Signals

The Digital Signal Processing workshop, 2005
Abstract In this paper we present a new method for adaptively decomposing a multicomponent signal into its components. This method is based on fitting an autoregressive (AR) model to the short-time spectra ofthe signal. The AR parameters represent the coefficients of the linear predictive (LP) polynomial. Theroots of this polynomial constitute a set of
K.T. Assaleh, R.J. Mammone
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Morphological signal decomposition

International Conference on Acoustics, Speech, and Signal Processing, 2002
A method of signal analysis is presented. It is based on mathematical morphology of gray scale functions. The proposed representations are translation invariant and use simple functions as the components of the representation. The analysis is unique and the signal can be reconstructed from its components.
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Automated decomposition of intramuscular electromyographic signals

IEEE Transactions on Biomedical Engineering, 2006
We present a novel method for extracting and classifying motor unit action potentials (MUAPs) from one-channel electromyographic recordings. The extraction of MUAP templates is carried out using a symbolic representation of waveforms, a common technique in signature verification applications. The assignment of MUAPs to their specific trains is achieved
Joël R, Florestal, Pierre A, Mathieu, Armando, Malanda   +2 more
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