Accession Number:

AD1064914

Title:

Optimization Techniques for Network Security, Distributed Agents, and RF Sensor Coexistence

Descriptive Note:

[Technical Report, Memorandum Report]

Corporate Author:

ARMY RESEARCH LAB ADELPHI MDARMY RESEARCH LAB ADELPHI MD

Personal Author(s):

• Weisman, Michael J.
• Martone, Anthony F.
• Verma, Gunjan
• Drost, Robert J.

Report Date:

2018-12-01

Pagination or Media Count:

22

Abstract:

A primary objective of the US Army Research Laboratory ARL is to bring together the scientific and military communities through collaboration on research that will directly benefit the Warfighter. A wide array of projects that ARL supports involves optimization of a noise-corrupted loss function over a potentially high-dimensional parameter space. In this report, we detail three areas of research that ARL is involved in that may benefit from stochastic optimization adversarial machine learning, distributed agents, and spectrum sensing for radar.

Descriptors:

• artificial neural networks
• machine learning
• radio frequency interference
• spectra
• communication channels
• military research
• power spectra
• algorithms
• frequency
• frequency bands
• learning
• multiobjective optimization
• optimization
• scattering
• bandwidth
• channel models
• diffraction
• information science
• radio frequency
• urban areas

Subject Categories:

• Radiofrequency Wave Propagation

Distribution Statement:

[A, Approved For Public Release]