This paper considers the statistical inference problem where both the hypothesis testing and
the parameter estimation are of primary interest. With unknown parameters present in each …

We treat the statistical inference problems in which one needs to detect the correct signal
model among multiple hypotheses and estimate a parameter simultaneously using as small …

In this paper, modulation classification and symbol decoding problems are jointly
considered and optimal strategies are proposed under various settings. In the considered …

This paper considers the problem of secure parameter estimation when an estimation
algorithm is prone to causative attacks. Causative attacks, in general, target decision-making …

Joint detection and estimation refers to deciding between two or more hypotheses and,
depending on the test outcome, simultaneously estimating the unknown parameters of the …

This paper considers the general state estimation in power systems when the system model
is not fully known. Model uncertainty might be caused by lack of full information about the …

The problem of joint detection and estimation under prior uncertainty is considered within
the framework of restricted Bayes theory, which covers the classical Bayes and minimax …

Joint decision and estimation (JDE) problems arise in a wide range of practical applications.
This work addresses the JDE problem in a distributed scenario using quantized data from …

Jointly testing multiple hypotheses and estimating a random parameter of the underlying
model is investigated in a sequential setup. The optimal scheme is designed such that it …

This paper presents an approach to multiple-model hypothesis testing (MMHT) based on 2-
SPRT (2-MMSRPT) for detecting unknown events that may have multiple possible …