Summary
International Technical Conference on Circuits/Systems, Computers and Communications
2008
Session Number:P2
Session:
Number:P2-73
Nonlinear Modeling of Super-Resolution Near Field Structure System based on the Volterra and Neural Network Models
Manjung Seo, Sungbin Im,
pp.-
Publication Date:2008/7/7
Online ISSN:2188-5079
Summary:
Reliable channel modeling becomes an important measure in performance evaluation on various data detection algorithms. For this reason, correct and accurate modeling is required. This paper presents a nonlinear modeling of Super-RENS (Super-Resolution Near Field Structure) read-out signal using the second-order Volterra and neural network models. The experiment results verified the possibility that Volterra and neural network models can be utilized for nonlinear modeling of Super-RENS systems. Furthermore, nonlinear equalizers can be developed based on the information obtained from this nonlinear modeling.