Cyclic Autocorrelation Function Toolbox

Resource Overview

Cyclic Autocorrelation Function Toolbox with custom implementation code examples (ex1-ex7) for signal processing applications.

Detailed Documentation

The Cyclic Autocorrelation Function Toolbox is a specialized MATLAB toolbox for time series data analysis, containing seven custom-coded implementation examples (ex1-ex7). This toolbox enables efficient computation of autocorrelation functions for time series data, featuring algorithms that implement sliding-window correlation analysis with configurable lag parameters. Key functions include data normalization routines and Fourier-based optimization methods for enhanced computational performance. Particularly useful in economics and meteorology applications, the toolbox incorporates preprocessing modules for data quality validation, ensuring high accuracy through outlier detection and trend removal algorithms. The implementation handles both stationary and non-stationary signals using cyclic statistic methods, with example codes demonstrating various correlation analysis techniques including cross-validation approaches.