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Unary coding

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Title: Unary coding  
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Subject: Golomb coding, Entropy encoding, Data compression, Instantaneously trained neural networks, Compression methods
Collection: Coding Theory, Data Compression, Lossless Compression Algorithms
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Unary coding

Unary coding

, sometimes called thermometer code, is an entropy encoding that represents a natural number, n, with n ones followed by a zero (if natural number is understood as non-negative integer) or with n − 1 ones followed by a zero (if natural number is understood as strictly positive integer). For example 5 is represented as 111110 or 11110. Some representations use n or n − 1 zeros followed by a one. The ones and zeros are interchangeable without loss of generality. Unary coding is both a Prefix-free code and a Self-synchronizing code.

n (non-negative) n (strictly positive) Unary code Alternative
0 1 0 1
1 2 10 01
2 3 110 001
3 4 1110 0001
4 5 11110 00001
5 6 111110 000001
6 7 1111110 0000001
7 8 11111110 00000001
8 9 111111110 000000001
9 10 1111111110 0000000001

Unary coding is an optimally efficient encoding for the following discrete probability distribution

\operatorname{P}(n) = 2^{-n}\,

for n=1,2,3,....

In symbol-by-symbol coding, it is optimal for any geometric distribution

\operatorname{P}(n) = (k-1)k^{-n}\,

for which k ≥ φ = 1.61803398879…, the golden ratio, or, more generally, for any discrete distribution for which

\operatorname{P}(n) \ge \operatorname{P}(n+1) + \operatorname{P}(n+2)\,

for n=1,2,3,.... Although it is the optimal symbol-by-symbol coding for such probability distributions, Golomb coding achieves better compression capability for the geometric distribution because it does not consider input symbols independently, but rather implicitly groups the inputs. For the same reason, arithmetic encoding performs better for general probability distributions, as in the last case above.

Contents

  • Unary code in use today 1
  • Unary coding in biological networks 2
  • Generalized unary coding 3
  • See also 4
  • References 5

Unary code in use today

Examples of unary code uses include:

  • In Golomb Rice code, unary encoding is used to encode the quotient part of the Golomb code word.
  • In UTF-8, unary encoding is used in the leading byte of a multi-byte sequence to indicate the number of bytes in the sequence, so that the length of the sequence can be determined without examining the continuation bytes.
  • Instantaneously trained neural networks use unary coding for efficient data representation.

Unary coding in biological networks

New research has shown that unary coding is used in the neural circuits responsible for birdsong production.[1][2] The nucleus in the brain of the songbirds that plays a part in both the learning and the production of bird song is the HVC (high vocal center). This coding works as space coding which is an efficient strategy for biological circuits due to its inherent simplicity and robustness.

Generalized unary coding

A generalized version of unary coding is able to represent numbers much more efficiently than standard unary coding.[3] Here's an example of generalized unary coding for integers from 1 through 15 that requires only 7 bits (where three bits are arbitrarily chosen in place of a single one in standard unary to show the number). Note that the representation is cyclic where one uses markers to represent higher integers in higher cycles.

n Unary code Generalized unary
0 0 0000000
1 10 0000111
2 110 0001110
3 1110 0011100
4 11110 0111000
5 111110 1110000
6 1111110 0010111
7 11111110 0101110
8 111111110 1011100
9 1111111110 0111001
10 11111111110 1110010
11 111111111110 0100111
12 1111111111110 1001110
13 11111111111110 0011101
14 111111111111110 0111010
15 1111111111111110 1110100

Generalized unary coding requires that the range of numbers to be represented be pre-specified because this range determines the number of bits that are needed.

See also

References

  1. ^ Fiete, I.R. and H.S. Seung, Neural network models of birdsong production, learning, and coding. New Encyclopediaof Neuroscience. Eds. L. Squire, T. Albright, F. Bloom, F. Gage, and N. Spitzer. Elsevier, 2007.
  2. ^ Moore J.M. et al., Motor pathway convergence predicts syllable repertoire size in oscine birds. Proc. Nat. Acad. Sc. USA 108: 16440-16445, 2011.
  3. ^ Kak, S., Generalized unary coding. Circuits, Systems and Signal Processing. 2015. http://link.springer.com/article/10.1007/s00034-015-0120-7#page-1


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