An introduction to signal detection and estimation (2nd ed.)

TL;DR: The problem of detecting extended targets when one or more target parameters of interest are unknown is treated and a composite hypothesis testing framework for jointly detecting the target along with such parameter estimation while only a finite number of signal samples are available is provided.

TL;DR: This work develops an observational model and finds a Cramér-Rao lower bound on the achievable square error performance of such a system, and proposes a two-stage inference architecture that uses a coarse estimate to select a subset of the sensor outputs for further processing, reducing the overall complexity of the system while achieving near-optimal performance.

TL;DR: A novel algorithm for the recognition and classification of human activities, which employs motion and color characteristics in a complementary manner, so as to extract the most information from both sources, and overcome their individual limitations.

TL;DR: In this paper, the authors propose a method to solve the problem of "uniformity" and "uncertainty" in the context of health care, and propose a solution.