STAR model - Revision history

en>Mcld: rm inappropriate headline detail ("calculated using R")

2014-10-09T13:11:39Z

rm inappropriate headline detail ("calculated using R")

← Older revision		Revision as of 15:11, 9 October 2014
Line 1:		Line 1:
	~~{{Otheruses4\|the transmission of data across noisy channels\|the storage of text in computers\|Variable-width encoding}}~~		The writer's name is Christy. I am truly fond of handwriting but I can't make it my occupation truly. I've usually cherished residing in Kentucky but now I'm contemplating other options. Invoicing is my occupation.<br><br>Also visit my site :: best psychic readings ([http://afeen.fbho.net/v2/index.php?do=/profile-210/info/ Test by click the "Remove Empty Lines" button and watch these blank lines between this text disappear.])
	~~In [[coding theory]] a '''variable-length code''~~' is ~~a [[code]] which maps source symbols to a ''variable'' number~~ of ~~bits.~~

	~~Variable-length codes~~ can ~~allow sources to be [[data compression\|compressed]] and decompressed with~~ ''~~zero~~'' error ([[lossless data compression]]) and still be read back symbol by symbol. With the right coding strategy an [[independent and identically-distributed random variables\|independent and identically-distributed source]] may be compressed almost arbitrarily close to its [[information entropy\|entropy]]. This is in contrast to fixed length coding methods, for which data compression is only possible for large blocks of data, and any compression beyond the logarithm of the total number of possibilities comes with a finite (though perhaps arbitrarily small) probability of failure.

	~~Some examples of well-known variable-length coding strategies are [[Huffman coding]], [[Lempel–Ziv\|Lempel–Ziv coding]] and [[arithmetic coding]]~~.

	~~== Codes and their extensions ==~~

	~~The extension of a code~~ is the mapping of finite length source sequences to finite length bit strings, that is obtained by concatenating for each symbol of the source sequence the corresponding codeword produced by the original code.

	~~Using terms from [[formal language theory]], the precise mathematical definition is as follows: Let~~ <~~math~~>S<~~/math~~> ~~and <math>T</math> be two finite sets, called the source and target [[alphabet (computer science)\|alphabets]], respectively. A '''code''' <math>C~~: ~~S \to T^</math> is a [[total function]] mapping each symbol from <math>S</math> to a [[Word~~ (~~data type)\|sequence of symbols]] over <math>T</math>, and the extension of <math>C</math> to a~~ [~~[Homomorphism#Homomorphisms_and_e-free_homomorphisms_in_formal_language_theory\|homomorphism]] of <math>S^</math> into <math>T^*<~~/~~math>, which naturally maps each sequence of source symbols to a sequence of target symbols, is referred to as its '''extension'''.~~

	~~== Classes of variable-length codes ==~~

	Variable-length codes can be strictly nested in order of decreasing generality as non-singular codes, uniquely decodable codes and prefix codes. Prefix codes are always uniquely decodable, and these in turn are always non-singular:

	~~=== Non-singular codes ===~~

	~~A code is '''non-singular''' if each source symbol is mapped to a different non-empty bit string, i.e. the mapping from source symbols to bit strings is [[injective]].~~
	* For example the mapping <math>M_1 = \{\, a\mapsto 0, b\mapsto 0, c\mapsto 1\,\}</~~math> is '''not''' non-singular because both "a" and "b" map to the same bit string "0" ; any extension of this mapping will generate a lossy (non-lossless) coding~~. Such singular coding may still be useful when some loss of information is acceptable (for example when such code is used in audio or video compression, where a lossy coding becomes equivalent to source [[Quantization (signal processing)\|quantization]]).
	* However, the mapping <math>M_2 = \{\, a \mapsto 1, b \mapsto 011, c\mapsto 01110, d\mapsto 1110, e\mapsto 10011\,\}</math> is non-singular ; its extension will generate a lossless coding, which will be useful for general data transmission (but this feature is not always required). Note that it is not necessary for the non-singular code to be more compact than the source (and in many applications, a larger code is useful, for example as a way to detect and/~~or recover from encoding or transmission errors, or in security applications to protect a source from undetectable tampering)~~.

	~~=== Uniquely decodable codes =~~==

	~~A code is '''uniquely decodable''' if its extension is non-singular. Whether a given code is uniquely decodable can be decided with the [[Sardinas–Patterson algorithm]].~~
	* The mapping <math>M_3 = \{\, a\mapsto 0, b\mapsto 01, c\mapsto 011\,\}</~~math> is uniquely decodable (this can be demonstrated by looking at the ''follow~~-set'' after each target bit string in the map, because each bitstring is terminated as soon as we see a 0 bit which cannot follow any existing code to create a longer valid code in the map, but unambiguously starts a new code).
	* Consider again the code <math>M_2</~~math> from the previous section. This code, which is based on an example found in,<ref>Berstel et al. (2009), Example 2.3.1, p. 63<~~/ref> is '''not''' uniquely decodable, since the string ''011101110011'' can be interpreted as the sequence of codewords ''01110–1110 – 011'', but also as the sequence of codewords ''011 – 1 – 011 – 10011''. Two possible decodings of this encoded string are thus given by ~~''cdb'' and ''babe''. However, such a code is useful when~~ the ~~set of all possible source symbols is completely known~~ and finite, or when there are restrictions (for example a formal syntax) that determine if source elements of this extension are acceptable. Such restrictions permit the decoding of the original message by checking which of the possible source symbols mapped to the same symbol are valid under those restrictions.

	~~=== Prefix codes ===~~
	~~{{Main\|Prefix code}}~~

	A code is a '''prefix code''' if no target bit string in the mapping is a prefix of the target bit string of a different source symbol in the same mapping. This means that symbols can be decoded instantaneously after their entire codeword is received. Other commonly used names for this ~~concept are '''prefix-free code''', '''instantaneous code''', or '''context-free code'''.~~
	* The example mapping <math>M_3</math> in the previous paragraph is '''not''' a prefix code because we don't know after reading the bit string "0" if it encodes a "a" source symbol, or if it is the prefix of the encodings of the "b" or "c" symbols.
	* An example of a prefix code is shown below.
	~~{\| class="wikitable" style="~~text~~-align:center; position: relative; left: 1in;" \|~~
	\|-
	~~! Symbol !! Codeword~~
	\|-
	~~\| a \|\| 0~~
	\|-
	~~\| b \|\| 10~~
	\|-
	~~\| c \|\| 110~~
	\|-
	~~\| d \|\| 111~~
	\|}
	~~:: Example of encoding and decoding:~~
	~~::: aabacdab → 00100110111010 → \|0\|0\|10\|0\|110\|111\|0\|10\| → aabacdab~~

	A special case of prefix codes are [[block code]]s. Here all codewords must have the same length. The latter are not very useful in the context of [[data compression\|source coding]], but often serve as [[forward error correction\|error correcting codes]] in the context of [[channel coding]].

	~~== Advantages ==~~

	The advantage of a variable-length code is that unlikely source symbols can be assigned longer codewords and likely source symbols can be assigned shorter codewords, thus giving a low [[Expected_value\|''expected'']~~] codeword length. For the above example, if the probabilities of (a, b, c, d~~) ~~were <math>\textstyle\left(\frac{1}{2}, \frac{1}{4}, \frac{1}{8}, \frac{1}{8}\right)</math>, the expected number of bits used to represent a source symbol using the code above would be:~~
	~~:: <math>1\times\frac{1}{2}+2\times\frac{1}{4}+3\times\frac{1}{8}+3\times\frac{1}{8}=\frac{7}{4}</math>.~~
	~~As the entropy of this source is 1.7500 bits per symbol, this code compresses the source as much as possible so that the source can be recovered with ''zero'' error.~~

	~~== Notes ==~~
	~~<references/>~~
	~~==References==~~
	* {{cite book \| last1=Berstel \| first1=Jean \| last2=Perrin \| first2=Dominique \| last3=Reutenauer \| first3=Christophe \| title=Codes and automata \| series=Encyclopedia of Mathematics and its Applications \| volume=129 \| location=Cambridge \| publisher=[[Cambridge University Press]] \| year=2010 \| isbn=978-0-521-88831-8 \| zbl=1187.94001 }} [http://www-igm.univ-mlv.fr/~berstel/LivreCodes/Codes.html Draft available online]

	~~{{Compression Methods}}~~

	~~[[Category:Coding theory]]~~
	~~[[Category:Lossless compression algorithms]]~~

en>Rasmus.p: minor fixes

2013-05-10T12:17:17Z

minor fixes

← Older revision		Revision as of 14:17, 10 May 2013
Line 1:		Line 1:
	~~Hi there~~. ~~Allow me begin~~ by ~~introducing~~ the ~~writer~~, ~~her name~~ is ~~Sophia~~. ~~Ohio~~ is ~~exactly where my home~~ is ~~but my spouse desires us~~ to ~~transfer~~. ~~Credit authorising~~ is ~~exactly where my main earnings comes~~ from. ~~To play lacross~~ is some ~~thing I truly appreciate doing~~.<br><br>~~my web page~~ - ~~free psychic~~ - [~~http:~~//~~srncomm~~.~~com~~/~~blog~~/~~2014~~/08/25/~~relieve~~-~~that~~-~~stress~~-~~find~~-a-~~new~~-~~hobby~~/ ~~mouse click the next page~~],		{{Otheruses4\|the transmission of data across noisy channels\|the storage of text in computers\|Variable-width encoding}}
			In [[coding theory]] a '''variable-length code''' is a [[code]] which maps source symbols to a ''variable'' number of bits.

			Variable-length codes can allow sources to be [[data compression\|compressed]] and decompressed with ''zero'' error ([[lossless data compression]]) and still be read back symbol by symbol. With the right coding strategy an [[independent and identically-distributed random variables\|independent and identically-distributed source]] may be compressed almost arbitrarily close to its [[information entropy\|entropy]]. This is in contrast to fixed length coding methods, for which data compression is only possible for large blocks of data, and any compression beyond the logarithm of the total number of possibilities comes with a finite (though perhaps arbitrarily small) probability of failure.

			Some examples of well-known variable-length coding strategies are [[Huffman coding]], [[Lempel–Ziv\|Lempel–Ziv coding]] and [[arithmetic coding]].

			== Codes and their extensions ==

			The extension of a code is the mapping of finite length source sequences to finite length bit strings, that is obtained by concatenating for each symbol of the source sequence the corresponding codeword produced by the original code.

			Using terms from [[formal language theory]], the precise mathematical definition is as follows: Let <math>S</math> and <math>T</math> be two finite sets, called the source and target [[alphabet (computer science)\|alphabets]], respectively. A '''code''' <math>C: S \to T^</math> is a [[total function]] mapping each symbol from <math>S</math> to a [[Word (data type)\|sequence of symbols]] over <math>T</math>, and the extension of <math>C</math> to a [[Homomorphism#Homomorphisms_and_e-free_homomorphisms_in_formal_language_theory\|homomorphism]] of <math>S^</math> into <math>T^*</math>, which naturally maps each sequence of source symbols to a sequence of target symbols, is referred to as its '''extension'''.

			== Classes of variable-length codes ==

			Variable-length codes can be strictly nested in order of decreasing generality as non-singular codes, uniquely decodable codes and prefix codes. Prefix codes are always uniquely decodable, and these in turn are always non-singular:

			=== Non-singular codes ===

			A code is '''non-singular''' if each source symbol is mapped to a different non-empty bit string, i.e. the mapping from source symbols to bit strings is [[injective]].
			* For example the mapping <math>M_1 = \{\, a\mapsto 0, b\mapsto 0, c\mapsto 1\,\}</math> is '''not''' non-singular because both "a" and "b" map to the same bit string "0" ; any extension of this mapping will generate a lossy (non-lossless) coding. Such singular coding may still be useful when some loss of information is acceptable (for example when such code is used in audio or video compression, where a lossy coding becomes equivalent to source [[Quantization (signal processing)\|quantization]]).
			* However, the mapping <math>M_2 = \{\, a \mapsto 1, b \mapsto 011, c\mapsto 01110, d\mapsto 1110, e\mapsto 10011\,\}</math> is non-singular ; its extension will generate a lossless coding, which will be useful for general data transmission (but this feature is not always required). Note that it is not necessary for the non-singular code to be more compact than the source (and in many applications, a larger code is useful, for example as a way to detect and/or recover from encoding or transmission errors, or in security applications to protect a source from undetectable tampering).

			=== Uniquely decodable codes ===

			A code is '''uniquely decodable''' if its extension is non-singular. Whether a given code is uniquely decodable can be decided with the [[Sardinas–Patterson algorithm]].
			* The mapping <math>M_3 = \{\, a\mapsto 0, b\mapsto 01, c\mapsto 011\,\}</math> is uniquely decodable (this can be demonstrated by looking at the ''follow-set'' after each target bit string in the map, because each bitstring is terminated as soon as we see a 0 bit which cannot follow any existing code to create a longer valid code in the map, but unambiguously starts a new code).
			* Consider again the code <math>M_2</math> from the previous section. This code, which is based on an example found in,<ref>Berstel et al. (2009), Example 2.3.1, p. 63</ref> is '''not''' uniquely decodable, since the string ''011101110011'' can be interpreted as the sequence of codewords ''01110–1110 – 011'', but also as the sequence of codewords ''011 – 1 – 011 – 10011''. Two possible decodings of this encoded string are thus given by ''cdb'' and ''babe''. However, such a code is useful when the set of all possible source symbols is completely known and finite, or when there are restrictions (for example a formal syntax) that determine if source elements of this extension are acceptable. Such restrictions permit the decoding of the original message by checking which of the possible source symbols mapped to the same symbol are valid under those restrictions.

			=== Prefix codes ===
			{{Main\|Prefix code}}

			A code is a '''prefix code''' if no target bit string in the mapping is a prefix of the target bit string of a different source symbol in the same mapping. This means that symbols can be decoded instantaneously after their entire codeword is received. Other commonly used names for this concept are '''prefix-free code''', '''instantaneous code''', or '''context-free code'''.
			* The example mapping <math>M_3</math> in the previous paragraph is '''not''' a prefix code because we don't know after reading the bit string "0" if it encodes a "a" source symbol, or if it is the prefix of the encodings of the "b" or "c" symbols.
			* An example of a prefix code is shown below.
			{\| class="wikitable" style="text-align:center; position: relative; left: 1in;" \|
			\|-
			! Symbol !! Codeword
			\|-
			\| a \|\| 0
			\|-
			\| b \|\| 10
			\|-
			\| c \|\| 110
			\|-
			\| d \|\| 111
			\|}
			:: Example of encoding and decoding:
			::: aabacdab → 00100110111010 → \|0\|0\|10\|0\|110\|111\|0\|10\| → aabacdab

			A special case of prefix codes are [[block code]]s. Here all codewords must have the same length. The latter are not very useful in the context of [[data compression\|source coding]], but often serve as [[forward error correction\|error correcting codes]] in the context of [[channel coding]].

			== Advantages ==

			The advantage of a variable-length code is that unlikely source symbols can be assigned longer codewords and likely source symbols can be assigned shorter codewords, thus giving a low [[Expected_value\|''expected'']] codeword length. For the above example, if the probabilities of (a, b, c, d) were <math>\textstyle\left(\frac{1}{2}, \frac{1}{4}, \frac{1}{8}, \frac{1}{8}\right)</math>, the expected number of bits used to represent a source symbol using the code above would be:
			:: <math>1\times\frac{1}{2}+2\times\frac{1}{4}+3\times\frac{1}{8}+3\times\frac{1}{8}=\frac{7}{4}</math>.
			As the entropy of this source is 1.7500 bits per symbol, this code compresses the source as much as possible so that the source can be recovered with ''zero'' error.

			== Notes ==
			<references/>
			==References==
			* {{cite book \| last1=Berstel \| first1=Jean \| last2=Perrin \| first2=Dominique \| last3=Reutenauer \| first3=Christophe \| title=Codes and automata \| series=Encyclopedia of Mathematics and its Applications \| volume=129 \| location=Cambridge \| publisher=[[Cambridge University Press]] \| year=2010 \| isbn=978-0-521-88831-8 \| zbl=1187.94001 }} [http://www-igm.univ-mlv.fr/~berstel/LivreCodes/Codes.html Draft available online]

			{{Compression Methods}}

			[[Category:Coding theory]]
			[[Category:Lossless compression algorithms]]

81.151.39.123: /* References */

2012-08-23T15:47:22Z

References

New page

Hi there. Allow me begin by introducing the writer, her name is Sophia. Ohio is exactly where my home is but my spouse desires us to transfer. Credit authorising is exactly where my main earnings comes from. To play lacross is some thing I truly appreciate doing.<br><br>my web page - free psychic - [http://srncomm.com/blog/2014/08/25/relieve-that-stress-find-a-new-hobby/ mouse click the next page],