Enumeration variables are defined here.

waveletID |
Wavelet name |

1 | Haar |

2 | Daubechies |

3 | Symlets |

4 | Coiflets |

5 | Biorthogonal spline |

6 | Reverse biorthogonal spline |

7 | Meyer |

8 | Discrete Meyer |

9 | Gaussian |

10 | Mexican hat |

11 | Morlet |

12 | Complex Gaussian |

13 | Complex Morlet |

14 | Complex Shannon |

15 | Complex frequency B-Spline |

Value |
Name |
Description |

1 | coefficients | Wavelet coefficients |

2 | signal | Reconstructed signal |

Value |
Name |
Description |

1 | fixedForm | Fixed form threshold. Threshold value = sqrt(2*ln(N)), with N being the length of the data to be denoised. |

2 | SURE | The threshold is calculated using the principle of Stein's Unbiased Risk Estimate(SURE). |

3 | heurSure | Heuristic SURE method. It is a combination of fixedForm and SURE methods. The noise level is firstly tested. For a high signal-to-noise ratio, SURE method is used, otherwise fixedForm method is used. |

4 | miniMax | The threshold is calculated according to the miniMax principle, which realizes the minimum of the maximum mean square error. |

Name | Description |
---|---|

mraDisplay | Selection of display data for MRA: 1 - wavelet coefficients; 2 - reconstructed signal |

threshMethod | Methods for calculating threshold for denoising: 1 - fixed form; 2 - SURE method; 3 - heuristic SURE; 4 - minimal maximum method |

wavletID | Definition of wavelet identifiers: 1 - Haar; 2 - Daubechies; 3 - Symlets; 4 - Coiflets; 5 - Biorthogonal spline; 6 - Reverse biorthogonal spline; 7 - Meyer; 8 - Discrete Meyer; 9 - Gaussian; 10 - Mexican hat; 11 - Morlet; 12 - Complex Gaussian; 13 - Complex Morlet; 14 - Complex Shannon; 15 - Complex frequency B-Spline |

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