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

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Table 12 Performance analysis of the proposed coif2 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	1.344408	0.0589	0.9847	0.1338	2.656092
2048	410	0.2	50	1024	15	2.311920	0.0542	0.9050	0.8674	2.634235
2048	512	0.25	50	1024	15	3.535317	0.0542	0.9052	0.8649	2.354271
2048	614	0.3	50	1024	15	4.017180	0.0531	0.8869	1.0428	2.595762
2048	849	0.4	50	1024	14	6.107924	0.0527	0.8812	1.0990	2.515127
2048	1024	0.5	50	1024	13	8.927963	0.0525	0.8773	1.1375	2.531853
2048	1229	0.6	50	1024	13	11.323331	0.0481	0.8035	1.9008	2.503729
2048	1434	0.7	50	1024	13	21.738856	0.0469	0.7832	2.1229	2.657620
2048	1536	0.75	50	1024	12	27.116146	0.0468	0.7817	2.1392	2.598041
2048	1638	0.8	50	1024	12	26.312156	0.0468	0.7816	2.1405	2.358481
2048	1843	0.9	50	1024	11	32.646767	0.0468	0.7816	2.1406	2.564254
2048	2048	1.0	50	1024	9	34.162602	0.0468	0.7815	2.1409	2.617750