coronoid: Ridge Estimation by Modified Corona Method

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

Ridge Estimation by Modified Corona Method

Description

Estimate a ridge using the modified corona method (modified cost function).

Usage

coronoid(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)

Arguments

tfrep	Estimate for the contribution of the noise to modulus.
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 derivative in cost function.
lambda	Coefficient of the ridge's second 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.

Details

To accelerate convergence, it is useful to preprocess modulus before running annealing method. Such a preprocessing (smoothing and subsampling of modulus) is implemented in coronoid. The parameter subrate specifies the subsampling rate.

Value

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.

Warning

The returned cost may be a large array. The argument costsub allows subsampling the cost function.

References

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

See Also

corona, icm, snake, snakoid.

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