Autocorrelation-Based Fundamental Frequency Extraction Algorithm with MATLAB Implementation

The MATLAB-based autocorrelation method for fundamental frequency extraction (combined with bandpass filtering and three-level clipping) is an algorithm designed to extract the fundamental frequency from signals. This implementation uses MATLAB as the programming platform and integrates bandpass filtering with three-level clipping technology. The primary objective of this algorithm is to accurately extract the fundamental frequency from input signals for subsequent analysis and processing. Through the autocorrelation approach, the algorithm precisely calculates the signal's fundamental frequency. The implementation typically involves computing the autocorrelation function using MATLAB's xcorr() function, followed by peak detection to identify the fundamental period. The bandpass filtering stage, often implemented using filter design functions like butter() or cheby1(), helps preprocess the signal by removing unwanted frequency components outside the range of interest. The three-level clipping technique serves as a nonlinear preprocessing step that simplifies the waveform while preserving essential pitch information, implemented through threshold-based signal conditioning. This enhanced methodology further optimizes extraction results by reducing harmonic interference and improving computational efficiency. The algorithm finds extensive applications in signal processing domains, particularly in audio processing and communication systems. It enables better understanding of signal frequency characteristics and provides valuable information for subsequent signal processing tasks. Key MATLAB functions involved in the implementation may include signal preprocessing routines, autocorrelation computation, peak detection algorithms, and frequency estimation modules.