Abstract
We present the algorithms necessary for the implementation of a quantum neural network with learning and classification tasks. A complete implementation for the classification and learning algorithms is given in terms of unitary quantum gates. Such a quantum neural network can be used to perform complex classification tasks or to solve the general problem of binary mapping.