View source: R/Crazy_Climbers.R

crc | R Documentation |

Uses the "crazy climber algorithm" to detect ridges in the modulus of a continuous wavelet or a Gabor transform.

crc(tfrep, tfspec=numeric(dim(tfrep)[2]), bstep=3, iteration=10000, rate=0.001, seed=-7, nbclimb=10, flag.int=TRUE, chain=TRUE, flag.temp=FALSE)

`tfrep` |
modulus of the (wavelet or Gabor) transform. |

`tfspec` |
numeric vector which gives, for each value of the scale or frequency the expected size of the noise contribution. |

`bstep` |
stepsize for random walk of the climbers. |

`iteration` |
number of iterations. |

`rate` |
initial value of the temperature. |

`seed` |
initial value of the random number generator. |

`nbclimb` |
number of crazy climbers. |

`flag.int` |
if set to TRUE, the weighted occupation measure is computed. |

`chain` |
if set to TRUE, chaining of the ridges is done. |

`flag.temp` |
if set to TRUE: constant temperature. |

Returns a 2D array called beemap containing the (weighted or unweighted) occupation measure (integrated with respect to time)

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

`corona`

, `icm`

, `coronoid`

,
`snake`

, `snakoid`

for ridge estimation,
`cfamily`

for chaining and
`crcrec`

,`gcrcrec`

,`scrcrec`

for
reconstruction.

data(HOWAREYOU) plot.ts(HOWAREYOU) cgtHOWAREYOU <- cgt(HOWAREYOU,70,0.01,100) clHOWAREYOU <- crc(Mod(cgtHOWAREYOU),nbclimb=1000)

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