View source: R/Ridge_Annealing.R

corona | R Documentation |

Estimate a (single) ridge from a time-frequency representation, using the corona method.

corona(tfrep, guess, tfspec=numeric(dim(tfrep)[2]), subrate=1, temprate=3, mu=1, lambda=2 * mu, iteration=1000000, seed=-7, stagnant=20000, costsub=1, plot=TRUE)

`tfrep` |
Time-Frequency representation (real valued). |

`guess` |
Initial guess for the algorithm. |

`tfspec` |
Estimate for the contribution of the noise to modulus. |

`subrate` |
Subsampling rate for ridge estimation. |

`temprate` |
Initial value of temperature parameter. |

`mu` |
Coefficient of the ridge's second derivative in cost function. |

`lambda` |
Coefficient of the ridge's derivative in cost function. |

`iteration` |
Maximal number of moves. |

`seed` |
Initialization of random number generator. |

`stagnant` |
Maximum number of stationary iterations before stopping. |

`costsub` |
Subsampling of cost function in output. |

`plot` |
When set(default), some results will be shown on the display. |

To accelerate convergence, it is useful to preprocess modulus before
running annealing method. Such a preprocessing (smoothing and
subsampling of modulus) is implemented in `corona`

. The
parameter subrate specifies the subsampling rate.

Returns the estimated ridge and the cost function.

`ridge` |
1D array (of same length as the signal) containing the ridge. |

`cost` |
1D array containing the cost function. |

The returned cost may be a large array, which is time consuming. The argument costsub allows subsampling the cost function.

See discussion in text of “Practical Time-Frequency Analysis”.

`icm`

,`coronoid`

,`snake`

, `snakoid`

.

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