MATLAB-Based Wiener Filter Implementation

This program presents an original implementation of a Wiener filter developed using MATLAB. The code is executable without modifications and serves as a valuable tool for those beginning their journey in digital signal processing. The Wiener filter is a fundamental signal processing technique designed to enhance signal quality under low signal-to-noise ratio conditions, with applications spanning speech processing, image enhancement, and radar signal analysis. The implementation follows Wiener's optimal filtering theory, employing statistical approaches to minimize mean-square error between estimated and desired signals. Key components include noise power estimation, signal autocorrelation computation, and frequency-domain filtering operations using MATLAB's built-in functions like fft, ifft, and xcorr. The algorithm automatically adapts to input signal characteristics through statistical calculations. Our design inspiration stems from both theoretical principles and practical applications of Wiener filtering. This program aims to help beginners better understand filter implementation methodologies, including critical aspects such as noise variance estimation, frequency response calculation, and real-time processing considerations. The code includes comments explaining each processing stage and parameter configuration options for different scenarios. Should you have any questions or suggestions regarding the implementation details or theoretical concepts, please feel free to contact us for technical discussion.