Linear Prediction Algorithm MATLAB Source Code from "Principles and Algorithms of Spatial Spectrum Estimation"

This document presents the linear prediction algorithm from "Principles and Algorithms of Spatial Spectrum Estimation" with complete MATLAB source code implementation. Linear prediction is a fundamental technique that estimates future signal values based on past observations, widely applied in speech processing, audio analysis, and data compression systems. The provided MATLAB code implements the core linear prediction algorithm using key functions such as lpc() for computing linear prediction coefficients and filter() for signal reconstruction. The implementation includes parameter optimization for different signal types and demonstrates how to calculate prediction errors using the Levinson-Durbin recursion algorithm. Readers can experiment with various signal inputs and adjust parameters like prediction order and windowing methods to observe their impact on spectrum estimation accuracy. The code structure follows modular design principles, separating coefficient calculation, signal prediction, and error analysis into distinct functions for easy modification and extension. Understanding these spatial spectrum estimation principles and the linear prediction algorithm enables applications across telecommunications, signal processing systems, and machine learning implementations where signal forecasting and spectrum analysis are required. The code includes comprehensive comments explaining each computational step and practical usage examples for different scenarios.