Experimental Analysis of Artificial Neural Networks Performance for Physical Activity Recognition Using Belt and Wristband Devices

2019 ◽  
Author(s):  
Jun Qi ◽  
Yun Yang ◽  
Xiyang Peng ◽  
Lee Newcombe ◽  
Andrew Simpson ◽  
...  
Keyword(s):  
Physical Activity ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Activity Recognition ◽  
Experimental Analysis ◽  
Physical Activity Recognition ◽  
Artificial Neural

scholarly journals Quantum enhanced cross-validation for near-optimal neural networks architecture selection

2018 ◽  
Vol 16 (08) ◽  
pp. 1840005 ◽  
Author(s):  
Priscila G. M. dos Santos ◽  
Rodrigo S. Sousa ◽  
Ismael C. S. Araujo ◽  
Adenilton J. da Silva
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Experimental Analysis ◽  
Cross Validation ◽  
Quantum Memory ◽  
Classical Algorithm ◽  
Artificial Neural ◽  
Quantum Speedup

This paper proposes a quantum-classical algorithm to evaluate and select classical artificial neural networks architectures. The proposed algorithm is based on a probabilistic quantum memory (PQM) and the possibility to train artificial neural networks (ANN) in superposition. We obtain an exponential quantum speedup in the evaluation of neural networks. We also verify experimentally through a reduced experimental analysis that the proposed algorithm can be used to select near-optimal neural networks.

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