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

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Table 28 Performance analysis of the random Gaussian 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	21	1.614613	0.0529	0.8846	0.6667	1.096733
2048	410	0.2	50	1024	22	3.101767	0.0506	0.8459	1.4526	0.748022
2048	512	0.25	50	1024	21	4.639830	0.0488	0.8163	1.6802	1.942504
2048	614	0.3	50	1024	20	5.067599	0.0488	0.8149	1.8149	2.142537
2048	849	0.4	50	1024	21	8.240858	0.0476	0.7949	2.0516	4.909329
2048	1024	0.5	50	1024	20	12.792057	0.0470	0.7847	2.1202	11.635789
2048	1229	0.6	50	1024	21	17.375626	0.0468	0.7817	2.1431	14.081669
2048	1434	0.7	50	1024	22	23.472323	0.0468	0.7816	2.1388	34.631693
2048	1536	0.75	50	1024	24	33.471279	0.0468	0.7816	2.1416	39.194676
2048	1638	0.8	50	1024	27	38.907176	0.0468	0.7816	2.1408	43.476185
2048	1843	0.9	50	1024	23	41.156261	0.0468	0.7816	2.1409	51.096753
2048	2048	1.0	50	1024	9	22.129988	0.0468	0.7815	2.1409	57.755398