Signal Processing for Communication Systems
Overfitting? Shrink your model! Regularization prevents memorization, enabling true learning & robust success. Discover how. A central problem in machine learning is to develop algorithms that work well both on training data and on new inputs (test data). Most machine learning tasks can be generalized as the estimation of a function \(\hat{f}(X)\) that maps the … Read more
Key focus: Know how to estimate unknown parameters using Ordinary Least Squares (OLS) method. As mentioned in the previous post, it is often required to estimate parameters that are unknown to the receiver. For example, if a fading channel is encountered in a communication system, it is desirable to estimate the channel response and cancel … Read more
“Mean Square Error”, abbreviated as MSE, is an ubiquitous term found in texts on estimation theory. Have you ever wondered what this term actually means and why is this getting used in estimation theory very often ? Any communication system has a transmitter, a channel or medium to communicate and a receiver. Given the channel … Read more