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

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Table 16 Performance analysis of the proposed sym4 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	1.426156	0.0606	1.0128	0.1101	2.219932
2048	410	0.2	50	1024	15	2.466473	0.0550	0.9186	0.7376	2.287469
2048	512	0.25	50	1024	15	4.034720	0.0550	0.9188	0.7360	2.408524
2048	614	0.3	50	1024	15	4.520797	0.0510	0.8516	1.3956	2.262042
2048	849	0.4	50	1024	14	6.883726	0.0503	0.8412	1.5016	2.461359
2048	1024	0.5	50	1024	14	9.275989	0.0503	0.8412	1.5015	2.600820
2048	1229	0.6	50	1024	13	10.699366	0.0479	0.8001	1.9374	2.083195
2048	1434	0.7	50	1024	13	13.702683	0.0468	0.7828	2.1269	2.117664
2048	1536	0.75	50	1024	12	16.142659	0.0468	0.7817	2.1393	2.303114
2048	1638	0.8	50	1024	12	17.024746	0.0468	0.7816	2.1405	2.259328
2048	1843	0.9	50	1024	12	21.118064	0.0468	0.7816	2.1406	2.369993
2048	2048	1.0	50	1024	9	21.227179	0.0468	0.7815	2.1409	2.248962