Nonlinear System Identification Using Robust Fusion Kernel-Based Radial basis function Neural Network-Reference-Cited by-同舟云学术

Nonlinear System Identification Using Robust Fusion Kernel-Based Radial basis function Neural Network

Published:2022-03-09 Issue: Volume: Page:
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Container-title:2022 International Conference on Emerging Smart Computing and Informatics (ESCI)
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Author:

Pattanaik Rakesh Kumar¹,Mohanty Mihir Narayan¹

Affiliation:

1. Siksha ‘O’ Anusandhan (Deemed to be University),ITER,Department of Electronics and Communication Engineering,Bhubaneswar,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9758147/9758153/09758338.pdf?arnumber=9758338

Reference15 articles.

1. Nonlinear System Identification Using Radial Basis Function-Based Signal-Dependent ARX Model

2. Sparse Bayesian Nonlinear System Identification Using Variational Inference

3. Modeling Nonlinear Processes Using the Radial Basis Function-Based State-Dependent Autoregressive Models

4. Improving the performance of radial basis function networks by learning center locations, in Advances in Neural Information Processing Systems;wettschereck;San Mateo CA,1992

5. A Novel Kernel for RBF Based Neural Networks

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