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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)
Returns a 2D array called beemap containing the (weighted or unweighted) occupation measure (integrated with respect to time)
modulus of the (wavelet or Gabor) transform.
numeric vector which gives, for each value of the scale or frequency the expected size of the noise contribution.
stepsize for random walk of the climbers.
number of iterations.
initial value of the temperature.
initial value of the random number generator.
number of crazy climbers.
if set to TRUE, the weighted occupation measure is computed.
if set to TRUE, chaining of the ridges is done.
if set to TRUE: constant temperature.
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.
corona
icm
coronoid
snake
snakoid
cfamily
crcrec
gcrcrec
scrcrec
data(HOWAREYOU) plot.ts(HOWAREYOU) cgtHOWAREYOU <- cgt(HOWAREYOU,70,0.01,100) clHOWAREYOU <- crc(Mod(cgtHOWAREYOU),nbclimb=1000)
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