Robust quantization with efficient WMSE search of a sign-shape codebook using illegal space

A method implemented by a computer system of searching a signed codebook to quantize an input vector representative of a portion of a signal, the signed codebook including a set of shape codevectors, each shape codevector being associated with a positive sign codevector and a negative signed codevector, comprising:

• (a) weighting, by a processor of the computer system, a shape codevector in the set of shape codevectors to produce a weighted shape;
• (b) correlating the weighted shape codevector with the input vector to produce a weighted correlation term, wherein the weighted correlation term has a single sign;
• (c) deriving a single minimization term for the shape codevector that corresponds to the positive signed codevector associated with the shape codevector when the sign of the weighted term is a first value
• (d) deriving a single minimization term for the shape codevector that corresponds to the negative signed codevector associated with the shape codevector when the sign of the weighted term is a second value;
• (e) performing steps (a), (b), (c) and (d) for each shape codevector in the set of shape codevectors, thereby deriving for each shape codevector either a first minimization term corresponding to the positive signed codevector or a second minimization term corresponding to the negative signed codevector associated with that shape codevector;
• and
• (f) selecting a preferred signed codevector from among the signed codevectors based on their corresponding minimization terms, wherein the preferred signed codevector represents a quantization corresponding to the input vector.

A method implemented by a computer system of searching a signed codebook to quantize an input vector representative of a portion of a signal, the signed codebook including a set of shape codevectors, each shape codevector being associated with a positive sign codevector and a negative signed codevector, comprising:

• (a) weighting, by a processor of the computer system, a shape codevector in the set of shape codevectors to produce a weighted shape codevector;
• (b) correlating the weighted shape codevector with the input vector to produce a weighted correlation term;
• Wherein the weighted correlation term has a single sign;
• (c) deriving a single minimization term for the shape codevector that corresponds to the positive signed codevector associated with the shape codevector when the sign of the weighted term is a first value;
• (d) deriving a single minimization term for the shape codevector that corresponds to the negative signed codevector associated with the shape codevector when the sign of the weighted term is a second value;
• (e) determining whether the positive codevector belongs to an illegal space representing illegal vectors when the weighted correlation term is first value;
• (f) determining whether the negative codevector belongs to the illegal space representing illegal vectors when the weighted correlation term is second value;
• (g) repeating steps (a) through (f) for each shape codevector;
• and
• (h) determining a best one of the positive and negative codevectors corresponding to minimization determined in steps (c) and (d) based on the minimization terms, the best codevector being a legal codevector.

A computer program product (CPP) comprising a computer usable medium having computer readable program code (CRPC) means embodied in the medium for causing an application program to execute on a computer processor to perform searching of a signed codebook to quantize an input vector representative of a portion of an input signal, the signed codebook including a set of shape codevectors, each shape codevector being associated with a positive signed codevector and a negative signed codevector, the CRPC means comprising:

• first CRPC means for causing the processor to weight a shape codevector in the set of shape codevectors with a weighting function for a Weighted Mean Square Error (WMSE) criteria, to produce a weighted shape codevector;
• second CRPC means for causing the processor to correlate the weighted shape codevector with the input vector to produce a weighted correlation term
• third CRPC means for causing the processor to determine, based on a sign of the weighted correlation term, a preferred one of the positive and negative signed codevectors associated with the shape codevector;
• and
• fourth CRPC means for causing the processor to derive a single minimization term for the shape codevector that corresponds to the preferred signed codevector.