Explore MATLAB source code curated for "系统辨识" with clean implementations, documentation, and examples.
RLS adaptive filter program for system identification with Gaussian white noise input, featuring detailed code comments and immediate execution capability. The implementation demonstrates real-time parameter adaptation using recursive least squares algorithm.
A MATLAB program implementing the recursive least squares algorithm for system identification, complete with execution results and graphical visualizations.
MATLAB programming examples for system identification techniques including Recursive Least Squares algorithm, Instrumental Variable method, Augmented Least Squares method, and Bias-Compensation method with code implementation details.
System identification using Recursive Least Squares method, including model building in Simulink environment and implementation source code with parameter estimation algorithms
System Identification with Recursive Least Squares Algorithm supporting online identification and real-time parameter estimation, featuring MATLAB implementation approaches
M-sequence signal algorithm simulation has broad application prospects in system identification. Compared with the multi-harmonic phase difference method, which requires prior knowledge of the number of identification parameters and complete cycle truncation for high precision, M-sequence signal testing imposes no such constraints. When identifying unknown models, the least squares algorithm can be utilized to observe the identification system's accuracy for determining model order. This algorithm not only provides computational methods for primitive polynomials used in M-sequence generation but also implements generation algorithms for M-sequence signals and develops corresponding identification methods.
MATLAB-based system identification program implementing least squares method - an advanced algorithm in automatic control featuring parameter estimation and model validation techniques.
Application of MATLAB in System Identification - Featuring source code implementation of the co-prime residue method with execution results including graphical outputs
This resource demonstrates MATLAB's application in system identification, featuring complete source code for M-sequence generation along with execution results including graphical outputs and algorithm analysis.
A practical recursive least squares identification program for system identification applications, implemented in MATLAB with efficient code structure and parameter estimation capabilities