Qubit Inspired Neural Network towards Its Practical Applications
Kentaro Mori, Teijiro Isokawa, Noriaki Kouda, Nobuyuki Matsui, H. Nishimura · The 2006 IEEE International Joint Conference on Neural Network Proceedings · 2006
Neural networks have attracted much interest in the two decades for their potential to describe brain function realistically. Quantum computing is a likely candidate for improving the computational efficiency of neural networks, since it has been very successful in doing so for a selected set of computational problems. We have proposed Qubit neural network that is a multilayered neural network composed of Qubit inspired neurons with Quantum Back Propagation learning and confirmed the performance concerning basic benchmark problems such as 4-bit and 6-bit parity check problems. In this paper, we examine this Qubit neural network through more practical problems, for example, the Iris data classification and the night vision processing.