Shape of a 1D Hann window:

Shape of a 2D Hann window:

Extract the continuous function representing the Hann window:

Parameterized Hann window:

Evaluate numerically:

Shape of a 1D Hann window using a specified parameter:

Variation of the shape as a function of the parameter α:

Translated and dilated Hann window:

2D Hann window with a circular support:

Discrete Hann window of length 15:

Discrete 15×10 2D Hann window:

Create a lowpass FIR filter with cutoff frequency of and length 21:

Taper the filter using a Hann window to improve stopband attenuation:

Normalize:

Log-magnitude plot of the power spectra of the two filters:

Filter a white noise signal using the Hann window method:

Use a window specification to calculate sample PowerSpectralDensity:

Calculate the spectrum:

Compare to spectral density calculated without a windowing function:

The plot shows that window smooths the spectral density:

Compare to the theoretical spectral density of the process:

Use a window specification for time series estimation:

Specify window for spectral estimator:

HannWindow[x,1] is equivalent to a Dirichlet window:

HannWindow[x,25/46] is equivalent to a Hamming window:

The area under the Hann window:

Normalize to create a window with unit area:

Fourier transform of the Hann window:

Power spectrum of the Hann window:

Discrete-time Fourier transform of the discrete Hann window of length 11:

Magnitude at ω=0:

Magnitude spectrum:

Power spectra of the Hann and rectangular windows:

2D sampling of Hann window will use a different parameter for each row of samples when passed as a symbol to Array:

Use a pure function instead: