Low complexity target vector identification

摘要

It is inter alia disclosed to identify one or more target vectors from a plurality of candidate vectors, each candidate vector having sorted elements and being associated with a respective class of one or more code vectors of a codebook and at least one of the candidate vectors being associated with a respective class of two or more code vectors that comprise the respective candidate vector and at least one code vector obtainable from the respective candidate vector by one of permutation and signed permutation, the target vectors having, among all candidate vectors of the plurality of candidate vectors, smallest distances towards a at least sorted representation of an input vector. The identifying comprises checking, for a candidate vector of the plurality of candidate vectors, at least based on a distance between the candidate vector and a reference vector and on a distance between the reference vector and the at least sorted representation of the input vector, if a distance between the at least sorted representation of the input vector and the candidate vector is larger than a distance between the at least sorted representation of the input vector and the reference vector. The identifying further comprises computing, for the candidate vector, the distance between the at least sorted representation of the input vector and the candidate vector only if the checking yields a negative result.

主权项

1. A method performed by an apparatus, said method comprising:
identifying one or more target vectors from a plurality of candidate vectors, each candidate vector having sorted elements and being associated with a respective class of one or more code vectors of a codebook and at least one of said candidate vectors being associated with a respective class of two or more code vectors that comprise said respective candidate vector and at least one code vector obtainable from said respective candidate vector by one of permutation and signed permutation, said target vectors having, among all candidate vectors of said plurality of candidate vectors, smallest distances towards a at least sorted representation of an input vector, said identifying comprising: checking, for a candidate vector of said plurality of candidate vectors, at least based on a distance between said candidate vector and a reference vector and on a distance between said reference vector and said at least sorted representation of said input vector, if a distance between said at least sorted representation of said input vector and said candidate vector is larger than a distance between said at least sorted representation of said input vector and said reference vector; and computing, when said checking yields a negative result for said candidate vector, a distance between said at least sorted representation of said input vector and said candidate vector, wherein a negative result is given when the distance between said at least sorted representation of said input vector and said candidate vector is not larger than a distance between said at least sorted representation of said input vector and said reference vector.