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8 Network Sciences
Pages 87-95

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From page 87...
... During each presentation the panel engaged in question-and-answer sessions with the presenter, and a general discussion with RDEC staff after the panel had formulated initial impressions and developed additional questions during its closed-session deliberations, conducted after the RDEC staff had concluded their presentations. AVIATION AND MISSILE RESEARCH, DEVELOPMENT, AND ENGINEERING CENTER The three AMRDEC projects that were presented during the review are Chaos in Linear and Piecewise-Linear Systems, Chaos in Optimal Communication and Radar Waveforms, and Optimal Signal Detection Using Mutual Information.
From page 88...
... There is opportunity for several significant practical applications as the PI has pointed out because, for example, the optical gain medium in a laser or optical amplifier can be modeled as a wave equation with gain, given that other applications range from combustion fronts, tsunamis, or infection waves in temporal-spatial epidemics. Given the theoretical results of this project, the challenge is to continue showing relevance to the Army by addressing real problems encountered by the soldier in the field or showing how to use chaos in proposing solutions that are simple to implement.
From page 89...
... Project: Optimal Signal Detection Using Mutual Information This project applies an innovative approach to bringing the power of classical information theory to statistical inference problems that address data streams that obey Markovian statistics. In its first year, the project has yielded one conference presentation and a draft paper for Physical Review Letters, a venue in which the PI has been publishing for nearly 20 years.
From page 90...
... As presently understood, information theory is a fundamental mathematical discipline dealing in asymptotic results on abstractly defined quantities. This funded ILIR project presents an opportunity to contribute to an applied theory of information, one that allows inferences to be made from finite data in addition to statements about theoretical limits.
From page 91...
... Project: Evaluation of Synthetic Infrared Environments for Training Deep Neural Nets This project focuses on using synthetically generated infrared (IR) images to train neural networks.
From page 92...
... Project: Radiating Structure and Loading Methodologies Versus l and d Reliant Approaches for Conformal Antenna System Design This work addresses research questions in antenna design, a basic research topic with both deep roots in physics and substantial implications for the Army. The focus of the analytic work is the study of the electromagnetic fields in the vicinity of the antenna, with the goal of understanding whether or not the use of metamaterials offers a fundamental advantage in the field strength -- for example, in the near field.
From page 93...
... The PI needs to present the work in widely attended, peer-reviewed conferences to obtain feedback on this work. CERDEC Crosscutting Findings For the project Evaluation of Synthetic IR Environments for Training Deep Neural Nets and other projects presented during the review, including Multimodal Content Delivery Using Resource Aware Artificial Intelligence, the PIs working on applying machine learning techniques to practical problems need to interact with one another extensively to share ideas, best practices, and research results.
From page 94...
... It is important to investigate how the detailed modeling of antennas and communications systems needs to be reflected in higher-layer network models. There are possible synergies between the research being performed on the Radiating Structure and Loading Methodologies versus m and e Reliant Approaches for Conformal Antenna System Design project and two other CERDEC ILIR projects -- Compressed Sensing with Massive Multiple Antenna (due to the interactions between the input and output combining algorithms and the antenna design)
From page 95...
... All the reviewed RDEC ILIR programs discussed in this chapter maintain and extend connectivity with outside academic institutions and industry. This ensures a steady level of intellectual exchange, cross-pollination, and timely feedback, which is necessary to support a high-quality research program.


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