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

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Table 9 Performance analysis of the proposed db9 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	15	1.252129	0.0583	0.9750	0.2203	2.649478
2048	410	0.2	50	1024	17	2.527130	0.0518	0.8660	1.2492	2.557930
2048	512	0.25	50	1024	17	3.972292	0.0518	0.8652	1.2582	2.531926
2048	614	0.3	50	1024	16	4.221050	0.0490	0.8182	1.7425	2.572460
2048	849	0.4	50	1024	15	6.270259	0.0478	0.7990	1.9495	2.683571
2048	1024	0.5	50	1024	14	9.593764	0.0478	0.7983	1.9571	2.533085
2048	1229	0.6	50	1024	13	11.075619	0.0470	0.7853	2.0992	2.499444
2048	1434	0.7	50	1024	13	14.518974	0.0468	0.7824	2.1309	2.539711
2048	1536	0.75	50	1024	12	17.178638	0.0468	0.7816	2.1405	2.489187
2048	1638	0.8	50	1024	12	18.043134	0.0468	0.7816	2.1406	2.506067
2048	1843	0.9	50	1024	12	22.370874	0.0468	0.7816	2.1407	2.569387
2048	2048	1.0	50	1024	9	22.751732	0.0468	0.7815	2.1409	2.497201