  In this paper, we present a new kind of learning implementation to recognize
the patterns using the concept of Mirroring Neural Network (MNN) which can
extract information from distinct sensory input patterns and perform pattern
recognition tasks. It is also capable of being used as an advanced associative
memory wherein image data is associated with voice inputs in an unsupervised
manner. Since the architecture is hierarchical and modular it has the potential
of being used to devise learning engines of ever increasing complexity.
