noiseless$52903$ - Definition. Was ist noiseless$52903$
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Was (wer) ist noiseless$52903$ - definition

DATA COMPRESSION THEORY
Shannon's noiseless coding theorem; Source coding theorem; Source Coding Theorem; Shannon's source coding Theorem; Shannon's source coding theorems; Shannon noiseless coding theorem; Shannon's first theorem

Fender Noiseless Pickups         
  • Eric Clapton
  • Fender Hot Noiseless
  • Fender N3 Noiseless pickups
  • Fender Lace Sensor pickups with a Dually
  • Jeff Beck
  • Vintage Noiseless Pickups
  • Tom Morello Montreux Jazz Festival 2005
Vintage Noiseless
The Fender Noiseless series is a line of electric guitar pickups made by the Fender Musical Instruments Corporation. Introduced in 1998, they feature a row of six (one for each guitar string) dual (opposite phase) stacked-coil (axially adjacent) pole pieces, designed to cancel hum noise.
The Noiseless Dead         
1946 FILM BY HUMBERTO GÓMEZ LANDERO
Hay muertos que no hacen ruido
The Noiseless Dead (Spanish: Hay muertos que no hacen ruido) is a 1946 Mexican comedy horror film directed by Humberto Gómez Landero and starring Germán Valdés, Marcelo Chávez and Amanda del Llano.Monsiváis & Kraniauskas p.
noiseless         
IMAGE NOISE REDUCTION APPLICATION
Draft:Noiseless
a.
Silent, inaudible, quiet.

Wikipedia

Shannon's source coding theorem

In information theory, Shannon's source coding theorem (or noiseless coding theorem) establishes the limits to possible data compression, and the operational meaning of the Shannon entropy.

Named after Claude Shannon, the source coding theorem shows that (in the limit, as the length of a stream of independent and identically-distributed random variable (i.i.d.) data tends to infinity) it is impossible to compress the data such that the code rate (average number of bits per symbol) is less than the Shannon entropy of the source, without it being virtually certain that information will be lost. However it is possible to get the code rate arbitrarily close to the Shannon entropy, with negligible probability of loss.

The source coding theorem for symbol codes places an upper and a lower bound on the minimal possible expected length of codewords as a function of the entropy of the input word (which is viewed as a random variable) and of the size of the target alphabet.