AN EFFICIENT EUCLIDEAN DISTANCE COMPUTATION FOR VECTOR QUANTIZATION USING A TRUNCATED LOOK-UP TABLE

Vector Quantizer (VQ) encoders generally use Euclidean distance measur e to encode the vectors. The major computation in the Euclidean distan ce is square (multiplication operation) of the difference between the vector components, This letter explores Euclidean distance computation and introduces a new technique which uses a truncated Look-Up Table ( LUT) to store a small set of repeatedly generated scalars. Specificall y, for numbers represented by m bits, this technique requires to store only 2(m) product terms instead of 2(m) x 2(m) product terms needed t o store in a conventional LUT.