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Considering an estimation problem of estimating a scalar deterministic parameter $a$ from the observations $y$ which are corrupted by randomvariable $w$. The observations are $y[n] = a + w[n]$ Least …

Based on document : Practical Approaches to Principal Component Analysis in the Presence of Missing Values The document explains probabilistic approach to principal component analysis using Maximum A …

The model is expressed as follows $$y(n) = \sum_{i=0}^{p-1} r(i) x(n-i) + v(n) \tag{1}$$ where $\mathbf{r} = \begin{bmatrix} r_1 & r_2 & \ldots &r_p \end{bmatrix}^T$ is the sparse length-$p$ vector c …

I am learning estimation theory and need help in understanding for educational purpose how the concept of ML works with the help of a step by step implementation. I am trying to find out the ML estim …

This question is an extension of another question of mine asked earlier here Help in understanding if the maximum likelhood estimation is working properly In that question the inputs were real valued …

I have an expression for the varaince of measurement noise obtained from an estimator. The measurement noise is additive white gaussian having values in complex domain. I have squared the term $(.)^2$ …

I am having difficulty in understanding how the Authors in this paper, An EM based method for semi blind identification of linear systems driven by Chaotic signals have used the expressions derived f …

I need to check if the estimation algorithm has converged or not. I am using the Maximum Likelihood estimation method. For convergence check, we see if the log-likelihood has reached its maximum value …