Indulal,G; Vijayakumar,A(Department of Mathematics, 2008)
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Abstract:
Eigenvalue of a graph is the eigenvalue of its adjacency matrix. The energy of a graph is the
sum of the absolute values of its eigenvalues. In this note we obtain analytic expressions for the
energy of two classes of regular graphs.
Mythili, P; Baby, Paul; Shanavaz, K T(IEEE, January 3, 2012)
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Abstract:
In this paper an attempt has been made to determine
the number of Premature Ventricular Contraction (PVC) cycles
accurately from a given Electrocardiogram (ECG) using a
wavelet constructed from multiple Gaussian functions. It is
difficult to assess the ECGs of patients who are continuously
monitored over a long period of time. Hence the proposed
method of classification will be helpful to doctors to determine
the severity of PVC in a patient. Principal Component Analysis
(PCA) and a simple classifier have been used in addition to the
specially developed wavelet transform. The proposed wavelet has
been designed using multiple Gaussian functions which when
summed up looks similar to that of a normal ECG. The number
of Gaussians used depends on the number of peaks present in a
normal ECG. The developed wavelet satisfied all the properties
of a traditional continuous wavelet. The new wavelet was
optimized using genetic algorithm (GA). ECG records from
Massachusetts Institute of Technology-Beth Israel Hospital
(MIT-BIH) database have been used for validation. Out of the
8694 ECG cycles used for evaluation, the classification algorithm
responded with an accuracy of 97.77%. In order to compare the
performance of the new wavelet, classification was also
performed using the standard wavelets like morlet, meyer,
bior3.9, db5, db3, sym3 and haar. The new wavelet outperforms
the rest
Description:
Power, Signals, Controls and Computation (EPSCICON), 2012 International Conference on,pp 1-5