Case Study: Implementation of Least Squares Algorithm with Forgetting Factor

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Resource Overview

A practical implementation case of the least squares algorithm with forgetting factor, including simulation models and M-files with detailed, easy-to-understand comments that demonstrate proper code structure and parameter configuration.

Detailed Documentation

This case study presents a simulation model implemented using the least squares algorithm with forgetting factor, accompanied by comprehensive M-files containing detailed code annotations. These comments facilitate clear understanding and practical application of the algorithm. The implementation demonstrates key aspects including recursive parameter updates, covariance matrix handling, and forgetting factor integration for adaptive system identification. Additionally, the case provides detailed explanations of the algorithm's theoretical background and practical application scenarios, enabling readers to better comprehend its advantages and limitations while effectively applying it to real-world problems. The code structure showcases proper initialization of covariance matrices, recursive weight updates, and forgetting factor implementation for handling time-varying systems.

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