A computational approach of interval estimation for information processing

Xinjia Chen

doi:10.1117/12.2579275

8 November 2020 A computational approach of interval estimation for information processing

Xinjia Chen

Proceedings Volume 11525, SPIE Future Sensing Technologies; 115251V (2020) https://doi.org/10.1117/12.2579275
Event: SPIE Future Sensing Technologies, 2020, Online Only

Conference Poster

Abstract

Interval estimation of data parameters is a frequent task of information processing for sensor systems. Classical parameter estimation methods for information processing suffer from the drawbacks of inaccuracy or conservatism. In this article, we propose a general method for constructing confidence regions for parameters of data. Moreover, we develop computable expressions on the minimum coverage probability of random intervals, which allows for a bisection coverage tuning method for constructing confidence intervals for parameters of various types of data. The proposed theory and algorithms can be applied to relevant tasks such as pattern classification, data fusion, target recognition and tracking.

Conference Presentation

Citation Download Citation

Xinjia Chen "A computational approach of interval estimation for information processing", Proc. SPIE 11525, SPIE Future Sensing Technologies, 115251V (8 November 2020); https://doi.org/10.1117/12.2579275

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