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Library / Signal processing and digital filters / DSP-12

Signal processing and digital filters

Hamming window sample

Coefficient n of the symmetric N-point Hamming window.

Ref
DSP-12
Rev
v1
Field
Signal processing and digital filters
Result
w[n]

The Hamming window w[n] = 0.54 − 0.46 cos(2πn/(N − 1)) has the same raised-cosine shape as Hann but with coefficients chosen to cancel the first sidelobe. This leaves nonzero end points of 0.08 and a slightly lower first sidelobe, at the cost of slower sidelobe decay.

Coefficient n of the symmetric N-point Hamming window. Its end points are nonzero (0.08), so it has a small edge discontinuity but lower first sidelobes than the Hann window. The page needs integers with 0 ≤ n ≤ N − 1.

Calculator

Solve for
samples
91,024
08
  • Position along the window, n/(N − 1)0.25
  • Value at the end points0.08
  • Value with the periodic convention (N in the denominator)0.4601

What drives the result

Each variable is moved across its typical range while the others stay at the values above. The longest bar is the key driver.

Window coefficient () current value 0.54
nSample indexKey driver
0.081
NWindow length
0.08
  • Sample 2 of a 9-point Hamming window is 0.54.
  • The ends never reach zero: they stay at 0.08, so a Hamming-windowed record has a small step at its edges.
Chart data as tables

Ranked variables

VariableTypical rangeLowest resultHighest resultSwing ()Local stepChange in result
n Sample index0 to 8 0.0810.92+1 +60.2 %
N Window length9 to 1,024 samples0.080030.540.46+1 samples−14.8 %

Sweep of Sample index

Sample indexWindow coefficient
00.08
10.2147
20.54
30.8653
41
50.8653
60.54
70.2147
80.08

Sweep one variable

Window coefficient ()Hover, touch, or use the arrow keys on the chart
0.20.40.60.81 02468 Sample index now 0.54

Variables and how each one contributes

w[n]

Window coefficient

Result ·

What the equation gives you. Everything else feeds it.

N

Window length

samples · typical 9 to 1,024

The window length, in samples. A longer window has more samples across the same shape, so a given n sits nearer the start. Raising it by 10 % (to 9.9) moves the result by −14.8 %, from 0.54 to 0.4601.

n

Sample index

· typical 0 to 8

The sample index, 0 to N − 1. Moves along the window from the start towards the centre and the other end. Raising it by 10 % (to 2.2) moves the result by +0 %, from 0.54 to 0.54.

Worked example with the values above

  1. Phase angle: 2πn/(N − 1) = 2π × 2 / 8 = 1.5708 rad.
  2. Cosine: cos(1.5708) = 6.1232×10−17.
  3. w = 0.54 − 0.46 × 6.1232×10−17 = 0.54.

Assumptions and limits

  • A symmetric N-point window with integer N ≥ 2 and 0 ≤ n ≤ N − 1, so the end points have the same value.
  • For periodic spectral analysis, replace N − 1 with N in the denominator.

Common mistakes

  • Using the symmetric form for spectral analysis, which assumes a periodic window.
  • Using an index outside 0 to N − 1.
  • Forgetting that Hamming and Kaiser (with β > 0) end points are not zero.

Statistics and uncertainty

Window coefficients are exact formulas, but sampled windows differ slightly between software packages (symmetric against periodic form), which changes the leakage figures in the fourth decimal place.

Where it is used

  • Generating window coefficients for FIR design and spectral estimation.
  • Trading main-lobe width against sidelobe level in tone measurements.

Maths you need

  • Spectral leakage: energy spreading into neighbouring bins
  • Sidelobe level: the height of the largest lobe outside the main lobe
  • Symmetric against periodic windows: N − 1 or N in the denominator

Related formulas

Practise this formula