Linear Features in Speech Signal Processing with MATLAB Implementation

In speech signal processing, linear feature extraction constitutes a fundamental computational task. Beyond conventional energy calculations, energy entropy serves as a widely employed characteristic parameter for signal analysis. To facilitate better understanding and practical application of this concept, I present below a MATLAB implementation for computing second-order energy entropy. The code demonstrates key signal processing techniques including: - Frame-based processing for segmenting speech signals - Energy calculation within each analysis frame - Probability distribution estimation of energy values - Entropy computation using logarithmic operations This implementation provides a practical reference for researchers and engineers working with speech feature extraction. The algorithm follows standard digital signal processing principles while maintaining computational efficiency through vectorized operations. Should you encounter any questions or require further clarification regarding the implementation details, please feel free to reach out for discussion.