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This paper describes an algorithm for verification of signatures written on a pen-input tablet. The algorithm is based on a novel, artificial neural network, called a" Siamese" neural network. This network consists of two identical sub-networks joined at their out (cid: 173) puts. During training the two sub-networks extract features from two signatures, while the joining neuron measures the distance be (cid: 173) tween the two feature vectors. Verification consists of comparing an extracted feature vector~ ith a stored feature vector for the signer. Signatures closer to this stored representation than a chosen thresh (cid: 173) old are accepted, all other signatures are rejected as forgeries.