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During almost three decades, the study on theory and applications of artificial neural network has increased considerably, due partly to a number of significant breakthroughs in research on network types and operational characteristics, but also because of some distinct advances in the power of computer hardware which is readily available for net implementation. In the last few years, recurrent neural networks (RNNs), which are neural network with feedback (closed-loop) connects, have been an important focus of research and development. Examples include bidirectional associative memory (BAM), Hopfield, cellular neural network (CNN), Boltzmann machine, and recurrent back propagation nets, etc.. RNN techniques have been applied to a wide variety of problems due to their dynamics and parallel distributed property, such as identifying and controlling the real-time system, neural computing, image processing and so on.

Recurrent Neural Network with Human Simulator Based Virtual Reality