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The two-dimensional parity-check code, usually called the optimal rectangular code, is the most popular form of multidimensional parity-check code. Assume that the goal is to transmit the four-digit message "1234", using a two-dimensional parity scheme. First the digits of the message are arranged in a rectangular pattern: 12 34
Formally, a parity check matrix H of a linear code C is a generator matrix of the dual code, C ⊥. This means that a codeword c is in C if and only if the matrix-vector product Hc ⊤ = 0 (some authors [1] would write this in an equivalent form, cH ⊤ = 0.) The rows of a parity check matrix are the coefficients of the parity check equations. [2]
With more than two qubits, additional parity measurements can be performed to determine if the qubits are the same value, and if not, to find which is the outlier. For example, in a system of three qubits, one can first perform a parity measurement on the first and second qubit, and then on the first and third qubit.
The parity-check matrix of a Hamming code is constructed by listing all columns of length r that are non-zero, which means that the dual code of the Hamming code is the shortened Hadamard code, also known as a Simplex code. The parity-check matrix has the property that any two columns are pairwise linearly independent.
A parity track was present on the first magnetic-tape data storage in 1951. Parity in this form, applied across multiple parallel signals, is known as a transverse redundancy check. This can be combined with parity computed over multiple bits sent on a single signal, a longitudinal redundancy check. In a parallel bus, there is one longitudinal ...
Checksum schemes include parity bits, check digits, and longitudinal redundancy checks. Some checksum schemes, such as the Damm algorithm , the Luhn algorithm , and the Verhoeff algorithm , are specifically designed to detect errors commonly introduced by humans in writing down or remembering identification numbers.
An example of problem in NC 1 is the parity check on a bit string. [6] The problem consists in counting the number of 1s in a string made of 1 and 0. A simple solution consists in summing all the string's bits.
Example: The linear block code with the following generator matrix is a [,,] Hadamard code: = ( ). Hadamard code is a special case of Reed–Muller code . If we take the first column (the all-zero column) out from G H a d {\displaystyle {\boldsymbol {G}}_{\mathrm {Had} }} , we get [ 7 , 3 , 4 ] 2 {\displaystyle [7,3,4]_{2}} simplex code , which ...