MATLAB Source Code for AIC System Identification Algorithm
- Login to Download
- 1 Credits
Resource Overview
Detailed Documentation
In this article, we explore the original MATLAB source code for the AIC (Akaike Information Criterion) system identification algorithm. We begin with a brief introduction to the background and conceptual framework of AIC-based system identification. The implementation process is then detailed, including key MATLAB functions such as data preprocessing, model parameter estimation, and AIC value calculation using the formula AIC = -2*log-likelihood + 2*number_of_parameters. Practical examples demonstrate how to apply the algorithm for model selection and validation. The discussion covers both advantages (automated model complexity control) and limitations (sensitivity to sample size), along with potential improvements like combining with cross-validation techniques. This comprehensive reference aims to assist researchers and practitioners in implementing efficient system identification solutions.
- Login to Download
- 1 Credits