Statistical Tests and Confidential Intervals as Thresholds for Quantum
Neural Networks
- URL: http://arxiv.org/abs/2001.11844v1
- Date: Thu, 30 Jan 2020 05:41:04 GMT
- Title: Statistical Tests and Confidential Intervals as Thresholds for Quantum
Neural Networks
- Authors: Do Ngoc Diep
- Abstract summary: We analyze and construct the least square quantum neural network (LS-QNN), the corresponding quantum neural network (PI-QNN), the regression quantum neural network (PR-QNN) and chi-squared quantum neural network ($chi2$-QNN)
We use the solution or tests as the threshold for the corresponding training rules.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Some basic quantum neural networks were analyzed and constructed in the
recent work of the author \cite{dndiep3}, published in International Journal of
Theoretical Physics (2020). In particular the Least Quare Problem (LSP) and the
Linear Regression Problem (LRP) was discussed. In this second paper we continue
to analyze and construct the least square quantum neural network (LS-QNN), the
polynomial interpolation quantum neural network (PI-QNN), the polynomial
regression quantum neural network (PR-QNN) and chi-squared quantum neural
network ($\chi^2$-QNN). We use the corresponding solution or tests as the
threshold for the corresponding training rules.
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