Hari Mohan Rai1,#, Chandra Mukherjee2,#, Joon Yoo1, Hanaa A. Abdallah3, Saurabh Agarwal4,*, Wooguil Pak4,*
CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5723-5745, 2025, DOI:10.32604/cmc.2025.070391
- 23 October 2025
Abstract A hybrid Compressed Sensing and Primal-Dual Wavelet (CSP-PDW) technique is proposed for the compression and reconstruction of ECG signals. The compression and reconstruction algorithms are implemented using four key concepts: Sparsifying Basis, Restricted Isometry Principle, Gaussian Random Matrix, and Convex Minimization. In addition to the conventional compression sensing reconstruction approach, wavelet-based processing is employed to enhance reconstruction efficiency. A mathematical model of the proposed algorithm is derived analytically to obtain the essential parameters of compression sensing, including the sparsifying basis, measurement matrix size, and number of iterations required for reconstructing the original signal and determining More >