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

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Table 19 Performance analysis of the proposed sym7 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	19	1.604935	0.0549	0.9178	0.7450	2.385164
2048	410	0.2	50	1024	16	2.270355	0.0530	0.8860	1.0514	2.368900
2048	512	0.25	50	1024	16	3.611425	0.0530	0.8857	1.0539	2.390055
2048	614	0.3	50	1024	14	3.719657	0.0494	0.8259	1.6620	2.400246
2048	849	0.4	50	1024	14	5.943942	0.0486	0.8126	1.8025	2.379669
2048	1024	0.5	50	1024	14	9.231755	0.0486	0.8125	1.8037	2.626292
2048	1229	0.6	50	1024	14	11.697056	0.0477	0.7968	1.9732	2.395632
2048	1434	0.7	50	1024	13	14.038048	0.0468	0.7824	2.1319	2.547235
2048	1536	0.75	50	1024	12	16.379478	0.0468	0.7816	2.1398	2.541034
2048	1638	0.8	50	1024	12	17.139381	0.0468	0.7816	2.1406	2.299743
2048	1843	0.9	50	1024	11	19.813613	0.0468	0.7816	2.1406	2.628218
2048	2048	1.0	50	1024	9	21.393741	0.0468	0.7815	2.1409	2.435649