He covers matched filtering, zero-forcing decision feedback equalization, linear equalization, minimum mean-square error and maximum likelihood decision feedback equalization, maximum likelihood sequence detection, advanced topics, and practical considerations.
What does ML stand for?
ML stands for Maximum Likelihood
This definition appears very frequently and is found in the following Acronym Finder categories:
- Science, medicine, engineering, etc.
See other definitions of ML
We have 134 other meanings of ML in our Acronym Attic
- Master Library
- Master Loot (Everquest, gaming)
- Master of Librarianship (degree program)
- Master's in Leadership
- Match Line
- Matched Lines (Nortel)
- Material Loss (corrosion)
- Materiel List
- MATLAB (software)
- Maturity Level
Samples in periodicals archive:
The authors describe the models and their properties, focusing on unstructured and structured antedependence individually, and then present inference procedures for the models in chapters that cover informal model identification via simple summary statistics and graphical methods, maximum likelihood and residual maximum likelihood estimation of parameters, likelihood ratio tests and penalized likelihood model selection criteria for the model's covariance structure, and mean structure.
This paper provides an Edgeworth expansion for the distribution of the maximum likelihood estimators (MLE) of the parameter of a time series generated by a linear regression model with Gaussian, stationary, long-memory errors.
Journals are typically kept as a continuous history for a few days covering the period of maximum likelihood for a data recovery action to occur.
Phylogenetic trees were produced with a maximum likelihood method incorporating the GTR+ [GAMMA]+I model of nucleotide substitution, with the general time-reversible (GTR) substitution matrix, the base composition, the gamma ([GAMMA]) distribution of among-site rate variation, and the proportion of invariant sites (I) all estimated from the data.
A maximum likelihood factor analysis with a varimax rotation yielded four factors: self-confidence; value of mathematics; enjoyment of mathematics; and motivation.
Maximum likelihood common factor analysis was used to determine the underlying dimensions of the scale.
Next, full information maximum likelihood techniques are used to estimate values of the parameters which maximize the likelihood (probability) of observing the data.