Consider a binary message vector m of length k and an (n, k) binary LDPC code.
The moments applied during the specific process are few and equal to the binary message length.
In a message of length LM there are LM-2 triples.
Aggregation counting is any procedure designed to solve the following problem: a number n of agents produces a fixed length binary message, and a central station produces an estimate of n from the bit-by-bit OR of the messages, which is therefore duplicate-insensitive.
In this work, the orthogonal moments ((M_{{pq}})) of the original image is used as the host signal, where the L-bit length binary message ((b_{mathrm {1}}), (b_{mathrm {2}}), …, (b_{{L}})) is inserted according to (2).
In Fig. 2, the original image corresponds to the host image where the L-bit length binary message ((b_{mathrm {1}}), (b_{mathrm {2}}), …, (b_{{L}})) is inserted, by constructing the final watermarked image.
Each A u is a binary vector of length.
Let us lexicographically order the binary sequences of length by (3).
Let "D" denote our ordered binary list of length N (the total number of gene transcripts).
A binary vector of length n therefore represents a single individual in the GA population.
