Complex Rotation Quantum Dynamic Neural Networks (CRQDNN) using Complex Quantum Neuron (CQN): Applications to time series prediction.
Quantum Neural Networks (QNN) models have attracted great attention since it innovates a new neural computing manner based on quantum entanglement. However, the existing QNN models are mainly based on the real quantum operations, and the potential of quantum entanglement is not fully exploited. In this paper, we proposes a novel quantum neuron model called Complex Quantum Neuron (CQN) that realizes a deep quantum entanglement. Also, a novel hybrid networks model Complex Rotation Quantum Dynamic Neural Networks (CRQDNN) is proposed based on Complex Quantum Neuron (CQN). CRQDNN is a three layer model with both CQN and classical neurons. An infinite impulse response (IIR) filter is embedded in the Networks model to enable the memory function to process time series inputs. The Levenberg-Marquardt (LM) algorithm is used for fast parameter learning. The networks model is developed to conduct time series predictions. Two application studies are done in this paper, including the chaotic time series prediction and electronic remaining useful life (RUL) prediction.
School of Reliability and Systems Engineering, Beihang University, Beijing, China; Science and Technology Key Laboratory on Reliability and Environmental Engineering, Beihang University, Beijing, China. Electronic address: yiqiancui@163.com.
Yiqian
Y
Cui
School of Reliability and Systems Engineering, Beihang University, Beijing, China; Science and Technology Key Laboratory on Reliability and Environmental Engineering, Beihang University, Beijing, China. Electronic address: shisjy@hotmail.com.
Junyou
J
Shi
School of Reliability and Systems Engineering, Beihang University, Beijing, China; Science and Technology Key Laboratory on Reliability and Environmental Engineering, Beihang University, Beijing, China. Electronic address: wangzili2014@yahoo.com.
Zili
Z
Wang
D000465:Algorithms; D003198:Computer Simulation; D003203:Computers, Hybrid; D005544:Forecasting; D000069550:Machine Learning; D016571:Neural Networks, Computer; D009474:Neurons; D011379:Prognosis; D011789:Quantum Theory; D012399:Rotation
Chaotic time series prediction; Complex Quantum Neuron (CQN); Infinite Impulse Response (IIR); Quantum entanglement; Remaining Useful Life (RUL) prediction