Please use this identifier to cite or link to this item:
https://dspace.iiti.ac.in/handle/123456789/378
Title: | Quantum inspired binary neural network algorithm |
Authors: | Patel, Om Prakash Tiwari, Aruna |
Keywords: | Backpropagation;Network layers;Neural networks;Neurons;Backpropagation learning;Binary neural networks;Classification accuracy;Generalization accuracy;Network structures;Number of iterations;Qubits;Training accuracy;Algorithms |
Issue Date: | 2014 |
Publisher: | Institute of Electrical and Electronics Engineers Inc. |
Citation: | Patel, O. P., & Tiwari, A. (2014). Quantum inspired binary neural network algorithm. Paper presented at the Proceedings - 2014 13th International Conference on Information Technology, ICIT 2014, 270-274. doi:10.1109/ICIT.2014.29 |
Series/Report no.: | CP11; |
Abstract: | In this paper a novel quantum based binary neural network learning algorithm is proposed. It forms three layer network structure. The proposed method make use of quantum concept for updating and finalizing weights of the neurons and it works for two class problem. The use of quantum concept form an optimized network structure. Also performance in terms of number of neurons and classification accuracy is improved. Same is compared with a quantum-based algorithm for optimizing artificial neural networks algorithm(QANN). It is found that there is improvement in the form of number of neurons at hidden layer, number of iterations, training accuracy and generalization accuracy. |
URI: | https://dspace.iiti.ac.in/handle/123456789/378 https://doi.org/10.1109/ICIT.2014.29 |
Type of Material: | Conference Paper |
Appears in Collections: | Department of Computer Science and Engineering |
Files in This Item:
File | Description | Size | Format | |
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CP11.pdf Restricted Access | 218.02 kB | Adobe PDF | View/Open Request a copy |
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