Parameter Estimation for Fractional Fourier Transform Applications

Parameter estimation and peak detection are crucial steps in Fractional Fourier Transform (FRFT) applications. In FRFT analysis, parameter estimation serves as a fundamental method for determining the fractional order and frequency components within signals. This typically involves implementing optimization algorithms to find the optimal transformation parameters that maximize signal energy concentration. Peak detection algorithms, such as local maximum search techniques or threshold-based methods, are employed to identify dominant peaks in the transformed domain, enabling better understanding of signal characteristics and properties. Common implementations include using gradient-based optimization for parameter estimation and employing noise-robust peak finding functions like findpeaks() in MATLAB or similar libraries in Python. Therefore, performing thorough parameter estimation and peak analysis before applying FRFT is essential. These preprocessing steps facilitate comprehensive signal analysis and processing, leading to more accurate transformation results and improved signal interpretation.