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Table 21 Performance analysis of the proposed sym9 wavelet based sensing matrix

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

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

17

1.433657

0.0582

0.9731

0.2364

2.566095

2048

410

0.2

50

1024

16

2.362390

0.0520

0.8695

1.2149

2.566405

2048

512

0.25

50

1024

16

3.703235

0.0520

0.8690

1.2191

2.529453

2048

614

0.3

50

1024

15

3.947898

0.0493

0.8243

1.6788

2.580208

2048

849

0.4

50

1024

14

5.824850

0.0481

0.8038

1.8975

2.566482

2048

1024

0.5

50

1024

13

8.527638

0.0481

0.8038

1.8973

2.627600

2048

1229

0.6

50

1024

12

9.961474

0.0470

0.7850

2.1023

2.621438

2048

1434

0.7

50

1024

12

12.963035

0.0468

0.7822

2.1333

2.582570

2048

1536

0.75

50

1024

12

16.468013

0.0468

0.7816

2.1406

2.628998

2048

1638

0.8

50

1024

11

15.820224

0.0468

0.7816

2.1406

2.705263

2048

1843

0.9

50

1024

11

19.915216

0.0468

0.7816

2.1407

2.695629

2048

2048

1.0

50

1024

9

21.477969

0.0468

0.7815

2.1409

2.618640