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

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Table 20 Performance analysis of the proposed sym8 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	1.337804	0.0591	0.9881	0.1037	2.398959
2048	410	0.2	50	1024	16	2.289342	0.0525	0.8775	1.1354	2.449329
2048	512	0.25	50	1024	16	3.605457	0.0525	0.8774	1.1361	2.413914
2048	614	0.3	50	1024	15	3.899311	0.0490	0.8194	1.7296	2.367131
2048	849	0.4	50	1024	14	5.839426	0.0489	0.8165	1.7613	2.414094
2048	1024	0.5	50	1024	14	9.219034	0.0489	0.8167	1.7590	2.477653
2048	1229	0.6	50	1024	13	10.916775	0.0476	0.7953	1.9899	2.412281
2048	1434	0.7	50	1024	13	14.105790	0.0468	0.7823	2.1324	2.411482
2048	1536	0.75	50	1024	12	16.337553	0.0468	0.7816	2.1403	2.425477
2048	1638	0.8	50	1024	11	15.876267	0.0468	0.7816	2.1406	2.452373
2048	1843	0.9	50	1024	11	19.838644	0.0468	0.7816	2.1406	2.439456
2048	2048	1.0	50	1024	9	21.412296	0.0468	0.7815	2.1409	2.481033