Signal Sampling with MATLAB: Undersampling, Oversampling, and Implementation Approaches

The MATLAB source code for signal sampling (including undersampling and oversampling) serves as a powerful educational and practical tool. This program enables deeper comprehension of signal processing concepts and principles through practical implementation, with applications spanning audio processing, image analysis, and communication systems. The code architecture allows users to configure sampling rates and filter parameters to achieve specific sampling effects, utilizing functions like 'resample' for rate conversion and 'fir1' for anti-aliasing filter design. Through proper parameter tuning, the program demonstrates how to prevent aliasing in undersampling scenarios and implement interpolation techniques for oversampling. The implementation also includes signal reconstruction capabilities using methods like sinc interpolation or polynomial fitting, allowing recovery of original signals from sampled data with enhanced accuracy. Understanding this codebase provides valuable insights for researchers and engineers working in signal processing and related fields, particularly through its demonstration of practical trade-offs between sampling frequency, bandwidth, and reconstruction fidelity.