Lecture notes on a linear form of power spectral density estimation in signal processing

In this lecture note, we relate some popular power density function (PDF) estimation methods to a unified and simple form to avoid student´s tedious sense. It is relatively more easily to understand and facilitates the comparison with each other. First, we reveal the criteria to design different PDF estimators, including periodogram method, MVDR (minimum variance distortless response) method, AR (auto regressive) method and MUSIC (multiple signal classification) method. In this way, students will be able to clearly see the means of optimization of the various algorithms. Then we will derive the solution to different optimization problem. Finally, we express the PDF estimation as a unified linear form to show essential differences of these methods to students.