Application of 1-D discrete wavelet transform based compressed sensing matrices for speech compression

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Table 13 Performance analysis of the proposed coif3 wavelet based sensing matrix

Length of signal (N)	Number of measurements (m)	Compression ratio (CR = m/N)	Sparsity level = (k/N) × 100 (%)	No. of non-zeros (k)	No. of iterations required	Signal reconstruction time (s)	RMSE	Relative error	SNR (db)	Construction time for sensing matrix (s)
2048	205	0.1	50	1024	16	1.313659	0.0561	0.9375	0.5604	3.076415
2048	410	0.2	50	1024	16	2.300134	0.0529	0.8835	1.0761	2.883624
2048	512	0.25	50	1024	16	3.836235	0.0529	0.8834	1.0770	2.977264
2048	614	0.3	50	1024	15	4.095096	0.0492	0.8228	1.6944	2.991658
2048	849	0.4	50	1024	14	6.307728	0.0485	0.8105	1.8244	2.734366
2048	1024	0.5	50	1024	14	12.427927	0.0485	0.8105	1.8247	3.000826
2048	1229	0.6	50	1024	13	14.180720	0.0475	0.7931	2.0136	2.732994
2048	1434	0.7	50	1024	13	26.695054	0.0468	0.7824	2.1319	2.674142
2048	1536	0.75	50	1024	12	23.379583	0.0468	0.7816	2.1403	2.967887
2048	1638	0.8	50	1024	11	19.402939	0.0468	0.7816	2.1406	2.882567
2048	1843	0.9	50	1024	11	25.077965	0.0468	0.7816	2.1406	2.741203
2048	2048	1.0	50	1024	9	30.924540	0.0468	0.7815	2.1409	2.949021