Explore MATLAB source code curated for "最小二乘辨识" with clean implementations, documentation, and examples.
Programs for generating random sequences, white noise generation techniques, M-sequence generation algorithms, along with least squares identification programs including batch processing for second-order systems, practical pressure system identification, recursive least squares methods, and augmented least squares identification approaches.
Key MATLAB implementations covering: 【1】Random sequence generation program 【2】White noise generation with zero mean and constant variance 【3】M-sequence generation with optimal autocorrelation properties 【4】One-step least squares identification for second-order systems 【5】Practical pressure system parameter identification 【6】Recursive least squares algorithm for large datasets 【7】Augmented least squares for underactuated systems 【8】Gradient-corrected least squares for enhanced accuracy 【9】Recursive maximum likelihood estimation 【10】Bayesian parameter estimation methods 【11】Modified neural network MBP algorithm for noisy systems 【12】Multi-dimensional nonlinear function identification 【13】Fuzzy neural network decoupling for multi-time-scale systems 【14】F-test procedures for model validation