Estimation of Nonlinear ARX Model for Soft Tissue by Wavenet and Sigmoid Estimators


  • M. A. Ayob Advanced Mechatronics Research Group (ADMIRE), Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia
  • W.N W. Zakaria Advanced Mechatronics Research Group (ADMIRE), Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia
  • J. Jalani Department of Electrical Engineering Technology, Faculty of Engineering Technology, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Batu Pahat, Johor, Malaysia
  • N. Mohamed Nasir Advanced Mechatronics Research Group (ADMIRE), Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia
  • M.R. Md Tomari Advanced Mechatronics Research Group (ADMIRE), Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia


System Identification, Soft Tissue Modeling, RV-2AJ, MATLAB, Simulink, Nonlinear ARX,


This paper presents a model-based design technique to estimate the dynamic model of a nonlinear soft tissue phantom using MATLAB Simulink. The soft tissue model was developed using black-box modeling approach; simulations were performed based on acquired set of single input-output data and processed using MATLAB System Identification toolbox. Wavenet and sigmoid estimators were used to acquire the best overall performance. Comparison study has been made between the simulation and experimental results. Our finding shows that the obtained model is sufficient to represent the model of soft tissue phantom with a mean error of 4.12% compared to the real system.


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How to Cite

Ayob, M. A., W. Zakaria, W., Jalani, J., Mohamed Nasir, N., & Md Tomari, M. (2016). Estimation of Nonlinear ARX Model for Soft Tissue by Wavenet and Sigmoid Estimators. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 8(7), 123–128. Retrieved from