series_ifft

You can use series_ifft when you want to reconstruct time-domain signals from frequency-domain data, implement frequency-domain filtering, or perform signal synthesis. This is particularly useful after applying frequency-domain operations like filtering or when you need to convert processed frequency data back to the original time domain. Typical applications include signal reconstruction, frequency-domain filtering, noise reduction, and advanced signal processing workflows.

Usage#

Syntax#

series_ifft(fft_real [, fft_imaginary])

Parameters#

Returns#

The function returns the complex inverse FFT in two series. The first series for the real component and the second one for the imaginary component.

Example#

The example below shows how series_ifft reverses the effect of series_fft by reconstructing the original time-domain signal from frequency-domain data.

Query

['sample-http-logs']
| summarize durations = make_list(req_duration_ms) by bin(_time, 1h)
| extend reconstructed_durations = series_ifft(series_fft(durations)[0])

Run in Playground

Output

List of related functions#

• series_fft: Performs Fast Fourier Transform to convert time domain to frequency domain. Use before applying frequency-domain operations.
• series_fir: Applies a finite impulse response filter to a series. Use for time-domain filtering instead of frequency-domain processing.
• series_cos: Returns the cosine of each element in an array. Use for generating periodic components in signal synthesis.
• series_sin: Returns the sine of each element in an array. Use for generating periodic components with phase shifts.
• series_exp: Calculates the exponential of each element in an array. Use for exponential signal components instead of frequency reconstruction.

Other query languages#