Recursive Least Squares Estimation (RLS) Algorithm

Efficient implementation for system identification using Recursive Least Squares (RLS) estimation. This algorithm is crucial for determining model order and parameter values. The program implements RLS to compute model order estimates and relevant parameter values with adaptive weight updates.

LC Low-Pass Butterworth Passive Filter Design

LC Low-Pass Butterworth Passive Filter Design - Automated calculation of LC component values based on specified parameters

Sliding Detrended Fluctuation Analysis (SDFA) Implementation with Parameter Optimization

Implementation of sliding detrended fluctuation analysis featuring comprehensive internal documentation. The MDFA configuration file allows adjustable parameters for optimized results. The variable 'x' contains EEG signal data (not included in upload). This modular algorithm can be adapted for various data types through parameter customization and includes configurable window sizing and detrending methodologies.