Sentence examples for parity constraints from inspiring English sources

Figure 1 shows the parity-check matrix of a very simple LDPC code with length bits and with parity constraints.

Given a large number of parity constraints with low weights, expander graph-based codes are natural candidates for codes to enable locality.

Note that their model can be generalized to ℓ≥2 erasures, and one can consider codes that enable successive local repairs from ℓ erasures by contacting ℓ parity constraints of weight at most (tilde {r} + 1).

Finally, conclusions are drawn in Section 9. LDPC codes are linear block-codes described by a parity-check matrix establishing a certain number of (even) parity constraints on the bits of a codeword.

In Figure 1, the diplotypes can be seen as the received message and the IBD indicators as the parity constraints, resulting in a MAP decoding algorithm similar to our Min-Sum algorithm.

In their model, they perform the repair of the two erasures in a successive manner, where a parity constraint of weight at most (tilde {r} + 1) is used to repair each of the two erasures.

The node c corresponds both to a parity check constraint between LDPC symbol nodes ((v_{1},dots,v_{d})) and to an RS linear constraint between all the symbol-nodes ((v_{1},dots,v_{d},e_{1,c},dots,e_{e(c),c})).

GLD codes which make the generalization of Gallager's LDPC codes are constructed by replacing the parity-check constraints in LDPC codes with block code constraints.

Another kind of coded chunked codes consists of chunks that satisfy some parity-check constraints, similar to those of LDPC codes.

Another class of such codes is L-chunked codes [17] which consider more general parity-check constraints and show better performance.

In Algorithm 1, is the th a priori LLR of the received bits, with and the length of the codeword, is the overall number of parity-check constraints, and the number of decoding iterations.