Reference MATLAB Code Examples for Signal Resampling - 2 Practical Implementations

These MATLAB resampling programs enable you to convert signals between different sampling frequencies, helping you better understand signal spectral characteristics. Below are two reference implementations with code-specific explanations:

1. Linear Interpolation Resampling Program:

This implementation uses linear interpolation for signal resampling, where new sample points are calculated as weighted averages between adjacent original samples. The algorithm maintains signal continuity by fitting straight lines between existing data points, effectively increasing or decreasing sampling frequency while preserving spectral resolution. Key MATLAB functions involved may include interp1 with 'linear' method parameter.

2. Nearest-Neighbor Interpolation Resampling Program:

This approach utilizes nearest-neighbor interpolation, where each new sample point adopts the value of the closest original sample. The method operates by directly copying or deleting sampling points through simple rounding operations, making it computationally efficient for real-time applications. Implementation typically involves MATLAB's resample function with zero-order hold characteristics.

These reference programs provide practical foundations for understanding and applying resampling techniques in digital signal processing workflows!