  We propose a framework for computer music composition that uses resilient
propagation (RProp) and long short term memory (LSTM) recurrent neural network.
In this paper, we show that LSTM network learns the structure and
characteristics of music pieces properly by demonstrating its ability to
recreate music. We also show that predicting existing music using RProp
outperforms Back propagation through time (BPTT).
