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

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Table 22 Performance analysis of the proposed sym10 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	17	1.479121	0.0560	0.9351	0.5831	2.708358
2048	410	0.2	50	1024	16	2.348326	0.0513	0.8578	1.3323	2.607475
2048	512	0.25	50	1024	16	3.762705	0.0513	0.8580	1.3298	2.729382
2048	614	0.3	50	1024	16	4.328904	0.0490	0.8192	1.7321	2.819432
2048	849	0.4	50	1024	14	6.057941	0.0479	0.8003	1.9353	2.719236
2048	1024	0.5	50	1024	14	9.516700	0.0479	0.8010	1.9273	2.715742
2048	1229	0.6	50	1024	13	11.268634	0.0470	0.7853	2.0992	2.484238
2048	1434	0.7	50	1024	12	13.607226	0.0468	0.7822	2.1333	2.680826
2048	1536	0.75	50	1024	12	17.225086	0.0468	0.7816	2.1405	2.634090
2048	1638	0.8	50	1024	12	18.192019	0.0468	0.7816	2.1406	2.628795
2048	1843	0.9	50	1024	12	22.716723	0.0468	0.7816	2.1406	2.709115
2048	2048	1.0	50	1024	9	22.909145	0.0468	0.7815	2.1409	2.612016