Quantum reflection

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Hann function with B = 1.50 (left), and its frequency response (right)

The Hann function, named after the Austrian meteorologist Julius von Hann, is a discrete window function given by

w(n)=0.5(1−cos⁡(2πnN−1))

or

w(n)=sin2(πnN−1)

or, in terms of the haversine function,

w(n)=haversin⁡(2πnN−1).

Spectrum

The Hann window is a linear combination of modulated rectangular windows wr=𝟏[0,N−1]. Thanks to the Euler formula

w(n)=12wr(n)−14ei2πnN−1wr(n)−14e−i2πnN−1wr(n)

Thanks to the basic properties of the Fourier transform, its spectrum is

ŵ(ω)=12ŵr(ω)−14ŵr(ω+2πN−1)−14ŵr(ω−2πN−1)

with the spectrum of the rectangular window

ŵr(ω)=e−iωN−12sin⁡(Nω/2)sin⁡(ω/2)

(the modulation factor vanished if windows are time-shifted around 0)

Name

Hann function is the original name, in honour of von Hann; however, the erroneous 'Hanning' function is also heard of on occasion, derived from the paper in which it was named, where the term "hanning a signal" was used to mean applying the Hann window to it. The confusion arose from the similar Hamming function, named after Richard Hamming.

Use

The Hann function is typically used as a window function in digital signal processing to select a subset of a series of samples in order to perform a Fourier transform or other calculations.

i.e. (using continuous version to illustrate)

S(τ)=∫w(t+τ)f(t)dt

The advantage of the Hann window is very low aliasing, and the tradeoff is slightly decreased resolution (widening of the main lobe). If the Hann window is used to sample a signal in order to convert to frequency domain, it is complex to reconvert to the time domain without adding distortions.

See also

References


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