| complex_demod {swdft} | R Documentation |
Complex Demodulation
Description
Complex Demodulation
Usage
complex_demod(x, f0, smooth = "butterworth", order = 5,
passfreq = 0.1, match_swdft = FALSE, window_size = NULL)
Arguments
x |
numeric vector |
f0 |
numeric scalar. Frequency to demodulate |
smooth |
character. Type of smoothing to use, accepts either 'ma', 'double_ma', or 'butterworth' (the default) |
order |
moving average parameter if 'smooth' argument equals 'ma' or 'double_ma'. Defaults to 5 |
passfreq |
numeric scalar. Pass frequency used in butterworth low-pass filter. Defaults to .1 which corresponds to a pass frequency of 2 * f0. |
match_swdft |
logical. Only used to demonstrate equivalence w/ SWDFT when a moving average filter is used. Otherwise, never used. |
window_size |
defaults to NULL, only used when match_swdft=TRUE, so can ignore. |
Value
An S3 'swdft_demod' object. See ?new_swdft_matching_demod for details.
References
Chapter 7 of 'Fourier Analysis of Time-Series' by Peter Bloomfield and this blog post: https://dankelley.github.io/r/2014/02/17/demodulation.html for the idea of using a butterworth filter.