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

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Table 17 Performance analysis of the proposed sym5 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	18	1.562108	0.0587	0.9813	0.1644	2.474725
2048	410	0.2	50	1024	16	2.410647	0.0525	0.8767	1.1428	2.422995
2048	512	0.25	50	1024	15	3.363769	0.0524	0.8764	1.1460	2.414940
2048	614	0.3	50	1024	14	3.633501	0.0487	0.8139	1.7885	2.401602
2048	849	0.4	50	1024	14	5.901087	0.0485	0.8100	1.8307	2.285970
2048	1024	0.5	50	1024	13	8.629663	0.0484	0.8094	1.8370	2.270979
2048	1229	0.6	50	1024	12	10.436658	0.0476	0.7951	1.9910	2.295386
2048	1434	0.7	50	1024	12	12.997505	0.0468	0.7825	2.1299	2.416593
2048	1536	0.75	50	1024	12	16.543217	0.0468	0.7816	2.1400	2.226996
2048	1638	0.8	50	1024	11	15.839222	0.0468	0.7816	2.1407	2.255090
2048	1843	0.9	50	1024	11	19.887183	0.0468	0.7816	2.1407	2.431380
2048	2048	1.0	50	1024	9	21.319450	0.0468	0.7815	2.1409	2.266367