Improved distance measure for pattern recognition

The Euclidean distance has often been used to measure the similarity between patterns represented by multidimensional vectors. The Euclidean distance is expensive to implement in hardware, and alternatives have been sought. The letter proposes a new distance measure which is a weighted sum of the city block and square distances. This new distance is a more accurate predictor of the Euclidean distance than are either of its components.