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{{Short description|Error-correcting code}}
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[[File:Hadamard-Code.svg|thumb|250 px|Matrix of the Augmented Hadamard code [32, 6, 16] for the [[Reed–Muller code]] (1, 5) of the NASA space probe [[Mariner 9]]]]
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The '''Hadamard code''' is an [[error-correcting code]] named after the French mathematician [[Jacques Hadamard]] that is used for [[error detection and correction]] when transmitting messages over very noisy or unreliable channels. In 1971, the code was used to transmit photos of Mars back to Earth from the NASA space probe [[Mariner 9]].<ref name="Malek_2006"/> Because of its unique mathematical properties, the Hadamard code is not only used by engineers, but also intensely studied in [[coding theory]], [[mathematics]], and [[theoretical computer science]].
The Hadamard code is also known under the names '''Walsh code''', '''Walsh family''',<ref name="Amadei-Manzoli-Merani_2002"/> and '''Walsh–Hadamard code'''<ref name="Arora-Barak_2009"/> in recognition of the American mathematician [[Joseph Leonard Walsh]].
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Since the relative distance of the Hadamard code is 1/2, normally one can only hope to recover from at most a 1/4 fraction of error. Using [[list decoding]], however, it is possible to compute a short list of possible candidate messages as long as fewer than <math>\frac{1}{2}-\epsilon</math> of the bits in the received word have been corrupted.
In [[code
==History==
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[[James Joseph Sylvester]] developed his construction of Hadamard matrices in 1867, which actually predates Hadamard's work on Hadamard matrices. Hence the name ''Hadamard code'' is disputed and sometimes the code is called ''Walsh code'', honoring the American mathematician [[Joseph Leonard Walsh]].
An augmented Hadamard code was used during the 1971 [[Mariner 9]] mission to correct for picture transmission errors. The
Because of limitations of the quality of the alignment of the transmitter at the time (due to Doppler Tracking Loop issues) the maximum useful data length was about 30 bits. Instead of using a [[repetition code]], a [32, 6, 16] Hadamard code was used.
Errors of up to 7 bits per 32-bit word could be corrected using this scheme. Compared to a 5-[[repetition code]], the error correcting properties of this Hadamard code are much better, yet its rate is comparable. The efficient decoding algorithm was an important factor in the decision to use this code.
The circuitry used was called the "Green Machine". It employed the [[fast Fourier transform]] which can increase the decoding speed by a factor of three. Since the 1990s use of this code by space programs has more or less ceased, and the [[NASA Deep Space Network]] does not support this error correction scheme for its dishes that are greater than 26 m.
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===Construction using a generator matrix===
The Hadamard code is a linear code, and all linear codes can be generated by a [[generator matrix]] <math>G</math>. This is a matrix such that <math>\text{Had}(x)= x\cdot G</math> holds for all <math>x\in\{0,1\}^k</math>, where the message <math>x</math> is viewed as a row vector and the vector-matrix product is understood in the [[vector space]] over the [[finite field]] <math>\mathbb F_2</math>. In particular, an equivalent way to write the inner product definition for the Hadamard code arises by using the generator matrix whose columns consist of ''all'' strings <math>y</math> of length <math>k</math>, that is,
:<math>G =
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===Proof of lemma 1===
Let <math>C(x) = c = (c_0,\dots,c_{2^n-1})</math> be the codeword in <math>C</math> corresponding to message <math>x</math>.
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===Proof of theorem 1===
To prove theorem 1 we will construct a decoding algorithm and prove its correctness.
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For each <math>i \in \{1, \dots, n\}</math>:
# Pick <math>j \in \{0, \dots, 2^n-1\}</math> uniformly at random.
# Pick <math>k \in \{0, \dots, 2^n-1\}</math> such that <math>j+k = e_i</math>, where <math>e_i</math> is the <math>i</math>-th [[standard basis|standard basis vector]] and <math>j+k</math> is the bitwise ''xor'' of <math>j</math> and <math>k</math>.
# <math>x_i \gets y_j+y_k</math>.
'''Output:''' Message <math>x = (x_1, \dots, x_n)</math>
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By lemma 1, <math>c_j+c_k = c_{j+k} = x\cdot g_{j+k} = x\cdot e_i = x_i</math>. Since <math>j</math> and <math>k</math> are picked uniformly, the probability that <math>y_j \not = c_j</math> is at most <math>\delta</math>. Similarly, the probability that <math>y_k \not = c_k</math> is at most <math>\delta</math>. By the [[union bound]], the probability that either <math>y_j</math> or <math>y_k</math> do not match the corresponding bits in <math>c</math> is at most <math>2\delta</math>. If both <math>y_j</math> and <math>y_k</math> correspond to <math>c</math>, then lemma 1 will apply, and therefore, the proper value of <math>x_i</math> will be computed. Therefore, the probability <math>x_i</math> is decoded properly is at least <math>1-2\delta</math>. Therefore, <math>\epsilon = \frac{1}{2} - 2\delta</math> and for <math>\epsilon</math> to be positive, <math>0 \leq \delta \leq \frac{1}{4}</math>.
Therefore, the Walsh–Hadamard code is <math>(2, \delta, \frac{1}{2}-2\delta)</math> locally decodable for <math>0\leq \delta \leq \frac{1}{4}</math>.
==Optimality==
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==References==
{{Reflist|refs=
<ref name="Malek_2006">{{cite book |title=Coding Theory |chapter=
<ref name="Amadei-Manzoli-Merani_2002">{{Cite book |title=Global Telecommunications Conference, 2002. GLOBECOM'02. IEEE |volume=1 |author-last1=Amadei |author-first1=M. |author-last2=Manzoli |author-first2=Umberto |author-last3=Merani |author-first3=Maria Luisa |chapter=On the assignment of Walsh and quasi-orthogonal codes in a multicarrier DS-CDMA system with multiple classes of users |publisher=[[IEEE]] |isbn=0-7803-7632-3 |doi=10.1109/GLOCOM.2002.1188196 |date=2002-11-17 |pages=841–845}}</ref>
<ref name="Arora-Barak_2009">{{Cite book |title=Computational Complexity: A Modern Approach |chapter=Section 19.2.2 |author-last1=Arora |author-first1=Sanjeev |author-link1=Sanjeev Arora |author-last2=Barak |author-first2=Boaz |publisher=[[Cambridge University Press]] |date=2009 |isbn=978-0-521-42426-4 |url=http://www.cs.princeton.edu/theory/complexity/}}</ref>
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[[Category:Coding theory]]
[[Category:Error detection and correction]]
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