Details

Title

Classification of EEG Signals Using Quantum Neural Network and Cubic Spline

Journal title

International Journal of Electronics and Telecommunications

Yearbook

2016

Volume

vol. 62

Issue

No 4

Authors

Divisions of PAS

Nauki Techniczne

Publisher

Polish Academy of Sciences Committee of Electronics and Telecommunications

Date

2016

Identifier

DOI: 10.1515/eletel-2016-0055 ; eISSN 2300-1933 (since 2013) ; ISSN 2081-8491 (until 2012)

Source

International Journal of Electronics and Telecommunications; 2016; vol. 62; No 4

References

Maojun Cao (2009), Fuhua Shang Quantum Neural Networks with application in adjusting PID parameters, IEEE. ; Dianbao Mu (2013), and others Learning Algorithm and Application of Quantum Neural Networks with Quantum Weights of Computer Theory and Engineering, International Journal, 5. ; Ajith Abraham (2005), Handbook of Measuring System Design Oklahoma State University Stillwater OK, USA. ; Professor (2010), Approximation by Spline Functions lecture of Computer University of Kentucky Lexington November, Science, 1. ; Saeid Sanei (2007), EEG signal processing Cardiff University, England. ; Daqi Zhu (2007), A Multi - layer Quantum Neural Networks Recognition System for Handwritten Digital Recognition, IEEE. ; David Friedman (2000), Event - Related Potential Studies of Memory Encoding and Retrieval Selective Microscopy Research and Technique New York, Review. ; Shicai Yu (2008), Quantum Neural Network and its Application in Vehicle Classification, IEEE. ; Gopathy Purushothaman (1997), Quantum Neural Networks Inherently Fuzzy Feedforward Neural Networks, IEEE, 8.
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