Hamming window - definitie. Wat is Hamming window
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Wat (wie) is Hamming window - definitie

FUNCTION USED IN SIGNAL PROCESSING
Window Function; Windowed frame; Window (signal processing); Apodization function; Rectangular window; Bartlett window; Triangular window; Bartlett-Hann window; Blackman window; Blackman-Harris window; Blackman-Nuttall window; Flat top window; Hamming window; Multiple overlap window; Triple overlapped cosine window; Gauss window; Sine window; Bessel window; Gaussian window; Bartlett function; Hamming function; Apodisation function; Hammingwindow; Windowing function; Barlett-Hann window; Windowing functions; Window functions; Tapering function; Tapering Function; Tapering (signal processing); Cosine window; De la Vallé Poussin window; De la Vallée Poussin window; Welch window; Bohman window; Boxcar window; Hann–Poisson window; Tukey window; Hann-Poisson window; DPSS window; List of window functions
  • Hann window]].  Most popular window functions are similar bell-shaped curves.
  • ''t''}} = 0.1}}
  • Bartlett–Hann window
  • Blackman–Harris window
  • Blackman–Nuttall window
  • Confined Gaussian window, ''σ''<sub>''t''</sub>&nbsp;=&nbsp;0.1
  • Sine window
  • DPSS window, ''α''&nbsp;=&nbsp;2
  • DPSS window, ''α''&nbsp;=&nbsp;3
  • Dolph–Chebyshev window, ''α''&nbsp;=&nbsp;5
  • Exponential window, ''τ''&nbsp;=&nbsp;(''N''/2)/(60/8.69)
  • Exponential window, ''τ''&nbsp;=&nbsp;''N''/2
  • GAP window (GAP optimized Nuttall window)
  • Gaussian window, ''σ''&nbsp;=&nbsp;0.4
  • Hamming window, ''a''<sub>0</sub>&nbsp;=&nbsp;0.53836 and ''a''<sub>1</sub>&nbsp;=&nbsp;0.46164. The original Hamming window would have ''a''<sub>0</sub>&nbsp;=&nbsp;0.54 and ''a''<sub>1</sub>&nbsp;=&nbsp;0.46.
  • Hann–Poisson window, ''α''&nbsp;=&nbsp;2
  • Kaiser window, ''α''&nbsp;=&nbsp;2
  • Kaiser window, ''α''&nbsp;=&nbsp;3
  • Sinc or Lanczos window
  • Nuttall window, continuous first derivative
  • Parzen window
  • Planck–Bessel window, ''ε''&nbsp;=&nbsp;0.1, ''α''&nbsp;=&nbsp;4.45
  • Planck-taper window, ''ε''&nbsp;=&nbsp;0.1
  • Rectangular window
  • 1=''α''&nbsp;=&nbsp;0.5}}
  • The Ultraspherical window's ''µ'' parameter determines whether its Fourier transform's side-lobe amplitudes decrease, are level, or (shown here) increase with frequency.
  • Welch window
  • Flat-top window
  • 1=''α''&nbsp;=&nbsp;0.16}}
  • Hann window
  • Triangular window (with ''L''&nbsp;=&nbsp;''N''&nbsp;+&nbsp;1)

Richard Hamming         
  • modulo]] 16, in the 16-color system.
AMERICAN MATHEMATICIAN AND INFORMATION THEORIST
Richard W. Hamming; Richard W Hamming; Richard Wesley Hamming; Hamming, Richard Wesley; Hamming, Richard; Richard Hammering; R. W. Hammering
<person> Professor Richard Wesley Hamming (1915-02-11 - 1998-01-07). An American mathematician known for his work in information theory (notably {error detection and correction}), having invented the concepts of Hamming code, Hamming distance, and Hamming window. Richard Hamming received his B.S. from the University of Chicago in 1937, his M.A. from the University of Nebraska in 1939, and his Ph.D. in mathematics from the University of Illinois at Urbana-Champaign in 1942. In 1945 Hamming joined the Manhattan Project at Los Alamos. In 1946, after World War II, Hamming joined the {Bell Telephone Laboratories} where he worked with both Shannon and John Tukey. He worked there until 1976 when he accepted a chair of computer science at the Naval Postgraduate School at Monterey, California. Hamming's fundamental paper on error-detecting and error-correcting codes ("Hamming codes") appeared in 1950. His work on the IBM 650 leading to the development in 1956 of the L2 programming language. This never displaced the workhorse language L1 devised by Michael V Wolontis. By 1958 the 650 had been elbowed aside by the 704. Although best known for error-correcting codes, Hamming was primarily a numerical analyst, working on integrating differential equations and the Hamming spectral window used for smoothing data before Fourier analysis. He wrote textbooks, propounded aphorisms ("the purpose of computing is insight, not numbers"), and was a founder of the ACM and a proponent of open-shop computing ("better to solve the right problem the wrong way than the wrong problem the right way."). In 1968 he was made a fellow of the {Institute of Electrical and Electronics Engineers} and awarded the Turing Prize from the Association for Computing Machinery. The Institute of Electrical and Electronics Engineers awarded Hamming the Emanuel R Piore Award in 1979 and a medal in 1988. http://www-gap.dcs.st-and.ac.uk/Richard Hamminghistory/Mathematicians/Hamming.html. http://zapata.seas.smu.edu/Richard Hamminggorsak/hamming.html. http://webtechniques.com/archives/1998/03/homepage/. [Richard Hamming. Coding and Information Theory. Prentice-Hall, 1980. ISBN 0-13-139139-9]. (2003-06-07)
Window function         
In signal processing and statistics, a window function (also known as an apodization function or tapering function) is a mathematical function that is zero-valued outside of some chosen interval, normally symmetric around the middle of the interval, usually near a maximum in the middle, and usually tapering away from the middle. Mathematically, when another function or waveform/data-sequence is "multiplied" by a window function, the product is also zero-valued outside the interval: all that is left is the part where they overlap, the "view through the window".
List of window functions         
In discrete-time signal processing, windowing is a preliminary signal shaping technique, usually applied to improve the appearance and usefulness of a subsequent Discrete Fourier Transform. Several window functions can be defined, based on a constant (rectangular window), B-splines, other polynomials, sinusoids, cosine-sums, adjustable, hybrid, and other types.

Wikipedia

Window function

In signal processing and statistics, a window function (also known as an apodization function or tapering function) is a mathematical function that is zero-valued outside of some chosen interval, normally symmetric around the middle of the interval, usually near a maximum in the middle, and usually tapering away from the middle. Mathematically, when another function or waveform/data-sequence is "multiplied" by a window function, the product is also zero-valued outside the interval: all that is left is the part where they overlap, the "view through the window". Equivalently, and in actual practice, the segment of data within the window is first isolated, and then only that data is multiplied by the window function values. Thus, tapering, not segmentation, is the main purpose of window functions.

The reasons for examining segments of a longer function include detection of transient events and time-averaging of frequency spectra. The duration of the segments is determined in each application by requirements like time and frequency resolution. But that method also changes the frequency content of the signal by an effect called spectral leakage. Window functions allow us to distribute the leakage spectrally in different ways, according to the needs of the particular application. There are many choices detailed in this article, but many of the differences are so subtle as to be insignificant in practice.

In typical applications, the window functions used are non-negative, smooth, "bell-shaped" curves. Rectangle, triangle, and other functions can also be used. A more general definition of window functions does not require them to be identically zero outside an interval, as long as the product of the window multiplied by its argument is square integrable, and, more specifically, that the function goes sufficiently rapidly toward zero.