Publication Type : Journal
Source : International Journal on Advanced Science, Engineering and Information
Url : https://core.ac.uk/outputs/296922127/?utm_source=pdf&utm_medium=banner&utm_campaign=pdf-decoration-v1
Campus : Coimbatore
School : School of Artificial Intelligence
Center : Center for Computational Engineering and Networking
Year : 2016
Abstract : It is well understood that in any data acquisition system reduction in the amount of data reduces the time and energy, but
the major trade-off here is the quality of outcome normally, lesser the amount of data sensed, lower the quality. Compressed Sensing
(CS) allows a solution, for sampling below the Nyquist rate. The challenging problem of increasing the reconstruction quality with
less number of samples from an unprocessed data set is addressed here by the use of representative coordinate selected from different
orders of splines. We have made a detailed comparison with 10 orthogonal and 6 biorthogonal wavelets with two sets of data from
MIT Arrhythmia database and our results prove that the Spline coordinates work better than the wavelets. The generation of two
new types of splines such as exponential and double exponential are also briefed here .We believe that this is one of the very first
attempts made in Compressed Sensing based ECG reconstruction problems using raw data.
Cite this Research Publication : Abhishek, S., S. Veni, and K. Narayanankutty. "Splines in Compressed Sensing." International Journal on Advanced Science, Engineering and Information Technology 6, no. 4 (2016): 469-476.