crc: Ridge Extraction by Crazy Climbers

In Rwave: Time-Frequency Analysis of 1-D Signals

Ridge Extraction by Crazy Climbers

Description

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

Usage

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)

Arguments

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.

Value

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

References

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

See Also

corona, icm, coronoid, snake, snakoid for ridge estimation, cfamily for chaining and crcrec,gcrcrec,scrcrec for reconstruction.

Examples

   data(HOWAREYOU)
 plot.ts(HOWAREYOU)
 
cgtHOWAREYOU <- cgt(HOWAREYOU,70,0.01,100)

clHOWAREYOU <- crc(Mod(cgtHOWAREYOU),nbclimb=1000)

Rwave documentation built on Oct. 22, 2022, 1:05 a.m.