An Objective-Based Experimental Design Framework for Signal Processing in the Context of Canonical Expansions Conference Paper

abstract

• 2017 IEEE. This work presents an objective-based experimental design framework for uncertainty reduction in filtering and signal processing when the underlying random processes are expressed in terms of canonical expansions. Canonical expansions are convenient representations for random processes that facilitate finding closed-form solutions for operators (filters). In the proposed experimental design framework, uncertainty is quantified based on the concept of mean objective cost of uncertainty, which measures uncertainty by taking into account the ultimate modeling objective, which is optimal filtering.

name of conference

• 2017 51st Asilomar Conference on Signals, Systems, and Computers

authors

• Qian, Xiaoning

published proceedings

• 2017 FIFTY-FIRST ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS

author list (cited authors)

• Dehghannasiri, R., Qian, X., & Dougherty, E. R.

citation count

• 0

complete list of authors

• Dehghannasiri, Roozbeh||Qian, Xiaoning||Dougherty, Edward R

publication date

• October 2017

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• Conference record / Asilomar Conference on Signals, Systems & Computers. Asilomar Conference on Signals, Systems & Computers  Journal

keywords

• Canonical Expansion
• Experimental Design
• Mean Objective Cost Of Uncertainty
• Robust Filter

Digital Object Identifier (DOI)

• 10.1109/acssc.2017.8335454

International Standard Book Number (ISBN) 13

• 9781538618233

start page

• 789

end page

• 793

volume

• 2017-October

URL

• http://dx.doi.org/10.1109/acssc.2017.8335454