About this document
ML Map by dvrprasana709 is a document available to read on EtoBox.
The document explains Maximum Likelihood (ML) and Maximum A Posteriori (MAP) detection in probability theory, detailing prior, likelihood, and posterior probabilities. ML detection maximizes the likelihood function to determine the most probable transmitted signal, while MAP detection incorporates prior probabilities to maximize the posterior probability. The Gaussian noise model leads to minimum distance detection for both methods, with MAP adjusting the decision rule based on prior probabilities.
- Author
- dvrprasana709
- Language
- EN