Identifying odd/even-order binary kernel slices for a nonlinear system using inverse repeat m-sequences

DOI10.1155/2015/454638zbMath1344.92064OpenAlexW1972987997WikidataQ35271138 ScholiaQ35271138MaRDI QIDQ308810

Gang Yan, Jin-yan Hu, Tao Wang

Publication date: 6 September 2016

Published in: Computational \& Mathematical Methods in Medicine (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2015/454638

zbMATH Keywords

cross-correlation methodinverse repeatm-sequencenonlinear binary kernel slices

Mathematics Subject Classification ID

Shift register sequences and sequences over finite alphabets in information and communication theory (94A55) Systems biology, networks (92C42)

Cites Work

• Unnamed Item
• Advances in Lee-Dchetzen method for Volterra filter identification
• On the generation of sequences simulating higher order white noise for system identification
• Block-oriented nonlinear system identification
• General methodology for nonlinear modeling of neural systems with Poisson point-process inputs
• A Unifying View of Wiener and Volterra Theory and Polynomial Kernel Regression

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