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FrM07.1 Proceeding of the 2004 American Control Conference Boston, Massachusetts June 30 July 2, 2004, Extended Recursive Least Squares Algorithm for Nonlinear Stochastic Systems Hooking Chen School
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What is extended recursive least squares?
Extended Recursive Least Squares (ERLS) is a mathematical algorithm used in signal processing and control systems to estimate the parameters of a system by recursively adjusting the estimates based on new incoming data. It is an extension of the Recursive Least Squares (RLS) algorithm and is particularly useful in situations where the system parameters might change over time.
Who is required to file extended recursive least squares?
Extended Recursive Least Squares (ERLS) is a computational algorithm used in signal processing and control systems. It is not a filing requirement for any individuals or organizations.
How to fill out extended recursive least squares?
Extended Recursive Least Squares (ERLS) is not a form or document that needs to be filled out. It is an algorithm used in mathematical calculations and programming.
What is the purpose of extended recursive least squares?
The purpose of Extended Recursive Least Squares (ERLS) is to estimate the parameters of a dynamic system by recursively updating the estimates based on new data. It is commonly used in applications such as adaptive filtering, system identification, and control systems to adjust the model parameters according to real-time measurements and observations.
What information must be reported on extended recursive least squares?
Extended Recursive Least Squares (ERLS) is a mathematical algorithm and does not involve reporting or collecting specific information. The algorithm operates on the data provided and does not require any input beyond the data itself.
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