Title :
Neural network based on QBP and its performance
Author :
Matsui, Nobuyuki ; Kouda, Noriaki ; Nishimura, Haruhiko
Author_Institution :
Dept. of Comput. Eng., Himeji Inst. of Technol., Hyogo, Japan
Abstract :
In recent years, some researchers have been exploring quantum computers in view of neural networks to realize a distributed and strongly connectionist system that achieves parallel and fast information processing. We (1998) have proposed and investigated a qubit neuron model based on quantum mechanics, and constructed the quantum backpropagation learning rule (QBP). In this paper, we show an improved QBP neural network model and discuss its performance on solving the 4 bit parity check problem and the function identification problem. Then, we conclude that our model is more effective than the conventional one in information processing efficiency
Keywords :
backpropagation; feedforward neural nets; parallel processing; performance evaluation; quantum theory; distributed connectionist system; feedforward neural networks; function identification; learning rule; parallel information processing; parity check problem; quantum backpropagation; quantum computers; quantum mechanics; qubit neuron model; Backpropagation; Computer networks; Concurrent computing; Distributed computing; Information processing; Neural networks; Neurons; Parity check codes; Quantum computing; Quantum mechanics;
Conference_Titel :
Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on
Conference_Location :
Como
Print_ISBN :
0-7695-0619-4
DOI :
10.1109/IJCNN.2000.861311
