Inverse hyperbolic function: Difference between revisions

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The '''Johnson bound''' is a limit on the size of [[error-correcting code]]s, as used in [[coding theory]] for [[data transmission]] or communications.
 
== Definition ==
Let <math>C</math> be a q-ary [[code]] of length <math>n</math>, i.e. a subset of <math>\mathbb{F}_q^n</math>. Let <math>d</math> be the minimum distance of <math>C</math>, i.e.
 
:<math>d = \min_{x,y \in C, x \neq y} d(x,y)</math>&nbsp;,
 
where <math>d(x,y)</math> is the [[Hamming distance]] between <math>x</math> and <math>y</math>.
 
Let <math>C_q(n,d)</math> be the set of all q-ary codes with length <math>n</math> and minimum distance <math>d</math> and let <math>C_q(n,d,w)</math> denote the set of codes in <math>C_q(n,d)</math> such that every element has exactly <math>w</math> nonzero entries.  
 
Denote by <math>|C|</math> the number of elements in <math>C</math>. Then, we define <math>A_q(n,d)</math> to be the largest size of a code with length <math>n</math> and minimum distance <math>d</math>:
 
:<math> A_q(n,d) = \max_{C \in C_q(n,d)} |C|.</math>
 
Similarly, we define <math>A_q(n,d,w)</math> to be the largest size of a code in <math>C_q(n,d,w)</math>:
 
:<math> A_q(n,d,w) = \max_{C \in C_q(n,d,w)} |C|.</math>
 
<strong>Theorem 1 (Johnson bound for <math>A_q(n,d)</math>):</strong>
 
If <math>d=2t+1</math>,
 
:<math> A_q(n,d) \leq \frac{q^n}{\sum_{i=0}^t {n \choose i} (q-1)^i + \frac{{n \choose t+1} (q-1)^{t+1} - {d \choose t} A_q(n,d,d)}{A_q(n,d,t+1)} }. </math>
 
If <math>d=2t</math>,
 
:<math> A_q(n,d) \leq \frac{q^n}{\sum_{i=0}^t {n \choose i} (q-1)^i + \frac{{n \choose t+1} (q-1)^{t+1} }{A_q(n,d,t+1)} }. </math>
 
<strong> Theorem 2 (Johnson bound for <math>A_q(n,d,w)</math>):</strong>
 
<strong>(i)</strong> If <math>d > 2w</math>,
 
:<math> A_q(n,d,w) = 1. </math>
 
<strong>(ii)</strong> If <math>d \leq 2w</math>, then define the variable <math>e</math> as follows. If <math>d</math> is even, then define <math>e</math> through the relation <math>d=2e</math>; if <math>d</math> is odd, define <math>e</math> through the relation <math>d = 2e - 1</math>. Let <math>q^* = q - 1</math>. Then,
 
:<math> A_q(n,d,w) \leq \lfloor \frac{n q^*}{w}  \lfloor \frac{(n-1)q^*}{w-1} \lfloor \cdots \lfloor \frac{(n-w+e)q^*}{e} \rfloor \cdots \rfloor \rfloor </math>
 
where <math>\lfloor ~~ \rfloor</math> is the [[floor function]].
 
<strong>Remark:</strong> Plugging the bound of Theorem 2 into the bound of Theorem 1 produces a numerical upper bound on <math>A_q(n,d)</math>.
 
==See also==
* [[Singleton bound]]
* [[Hamming bound]]
* [[Plotkin bound]]
* [[Elias Bassalygo bound]]
* [[Gilbert–Varshamov bound]]
* [[Griesmer bound]]
 
==References==
* S. M. Johnson, "A new upper bound for error-correcting codes," ''IRE Transactions on Information Theory'', pp.&nbsp;203–207, April 1962.
* W. Cary Huffman, [[Vera Pless]], ''Fundamentals of Error-Correcting Codes'', Cambridge University Press, 2003.
 
[[Category:Coding theory]]

Revision as of 13:41, 17 November 2013

The Johnson bound is a limit on the size of error-correcting codes, as used in coding theory for data transmission or communications.

Definition

Let be a q-ary code of length , i.e. a subset of . Let be the minimum distance of , i.e.

 ,

where is the Hamming distance between and .

Let be the set of all q-ary codes with length and minimum distance and let denote the set of codes in such that every element has exactly nonzero entries.

Denote by the number of elements in . Then, we define to be the largest size of a code with length and minimum distance :

Similarly, we define to be the largest size of a code in :

Theorem 1 (Johnson bound for ):

If ,

If ,

Theorem 2 (Johnson bound for ):

(i) If ,

(ii) If , then define the variable as follows. If is even, then define through the relation ; if is odd, define through the relation . Let . Then,

where is the floor function.

Remark: Plugging the bound of Theorem 2 into the bound of Theorem 1 produces a numerical upper bound on .

See also

References

  • S. M. Johnson, "A new upper bound for error-correcting codes," IRE Transactions on Information Theory, pp. 203–207, April 1962.
  • W. Cary Huffman, Vera Pless, Fundamentals of Error-Correcting Codes, Cambridge University Press, 2003.