6 papers
Asynchronous Online Adaptation via Modular Drift Detection for Deep Receivers
Nicole Uzlaner, Tomer Raviv, Nir Shlezinger +1
Deep learning is envisioned to facilitate the operation of wireless receivers, with emerging architectures integrating deep neural networks (DNNs) with traditional modular receiver…
Performance Analysis of LMS Filters with non-Gaussian Cyclostationary Signals
Nir Shlezinger, Koby Todros
The least mean-square (LMS) filter is one of the most common adaptive linear estimation algorithms. In many practical scenarios, and particularly in digital communications systems,…
Measure Transformed Quasi Score Test with Application to Location Mismatch Detection
Koby Todros
In this paper, we develop a generalization of the Gaussian quasi score test (GQST) for composite binary hypothesis testing. The proposed test, called measure transformed GQST (MT-G…
Binary Hypothesis Testing via Measure Transformed Quasi Likelihood Ratio Test
Nir Halay, Koby Todros, Alfred O. Hero
In this paper, the Gaussian quasi likelihood ratio test (GQLRT) for non-Bayesian binary hypothesis testing is generalized by applying a transform to the probability distribution of…
Measure-Transformed Quasi Maximum Likelihood Estimation
Koby Todros, Alfred O. Hero
In this paper the Gaussian quasi maximum likelihood estimator (GQMLE) is generalized by applying a transform to the probability distribution of the data. The proposed estimator, ca…
Robust Multiple Signal Classification via Probability Measure Transformation
Koby Todros, Alfred O. Hero
In this paper, we introduce a new framework for robust multiple signal classification (MUSIC). The proposed framework, called robust measure-transformed (MT) MUSIC, is based on app…