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Trevor J. Bihl
Wright State University
Machine learningEngineeringFeature selectionComputer scienceArtificial neural network
41Publications
6H-index
132Citations
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Publications 53
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#2Aaron M. Jones (AFRL: Air Force Research Laboratory)H-Index: 5
Last. Ashley DeMange (AFRL: Air Force Research Laboratory)
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Neuromorphic computing hardware mimics neurobiological architectures and promises eventual low power operation. Additionally, arbitrary waveform generator hardware permits the realization of complex radar waveform structures. In this paper, we combine these two technologies and investigate the potential of spiking neural networks to generate radar waveforms and their suitability in dynamic environments where adaptability is paramount. We discuss the process of development, current limitations, a...
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#1Trevor J. Bihl (AFRL: Air Force Research Laboratory)H-Index: 6
#2Todd J. Paciencia (AFIT: Air Force Institute of Technology)H-Index: 1
Last. Michael A. Temple (AFIT: Air Force Institute of Technology)H-Index: 26
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Radio frequency (RF) fingerprinting extracts fingerprint features from RF signals to protect against masquerade attacks by enabling reliable authentication of communication devices at the “serial number” level. Facilitating the reliable authentication of communication devices are machine learning (ML) algorithms which find meaningful statistical differences between measured data. The Generalized Relevance Learning Vector Quantization-Improved (GRLVQI) classifier is one ML algorithm which has sho...
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#1Trevor J. Bihl (Wright State University)H-Index: 6
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#1Trevor J. Bihl (Wright State University)H-Index: 6
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#1Trevor J. Bihl (Wright State University)H-Index: 6
#2Robert J Gutierrez (AFIT: Air Force Institute of Technology)
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#1Jayson Boubin (OSU: Ohio State University)
#2Aaron M. Jones (AFRL: Air Force Research Laboratory)H-Index: 5
Last. Trevor J. Bihl (AFRL: Air Force Research Laboratory)H-Index: 6
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Vehicular Ad-Hoc networks depend on clear communication between vehicles using radio frequency in order to operate effectively. Interference from existing technologies using the RF spectrum, e.g. IoT devices, UAV, mobile systems, calls into question the feasibility of future VANET systems without an ability to cut through the noise. One approach to overcome interference is to use waveform design to provide this capability. Regrettably, most traditional algorithms are too computationally complex ...
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#1Peter John-Baptiste (OSU: Ohio State University)H-Index: 1
#2J. Mylroie-Smith (OSU: Ohio State University)H-Index: 139
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In this paper, we discuss the feasibility of the novel application of recurrent neural networks (RNN) in designing low-latency, near-optimal radar waveforms in dynamical environments. Traditional approaches to adaptive radar waveform design typically require cumbersome optimization routines and highly specialized solvers that can be slow to converge. In an effort to decrease the time of convergence, while still being robust to dynamic environments and practical implementation concerns, we provid...
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#1Jeffrey B. Travers (Wright State University)H-Index: 38
#2Chien Poon (Wright State University)H-Index: 2
Last. Ulas Sunar (Wright State University)H-Index: 15
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We investigated the change in optical properties and vascular parameters to characterize skin tissue from mild photodamage to actinic keratosis (AK) with comparison to a published photodamage scale. Multi-wavelength spatial frequency domain imaging (SFDI) measurements were performed on the dorsal forearms of 55 adult subjects with various amounts of photodamage. Dermatologists rated the levels of photodamage based upon the photographs in blinded fashion to allow comparison with SFDI data. For ch...
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Jul 17, 2019 in AAAI (National Conference on Artificial Intelligence)
#1Trevor J. Bihl (Wright State University)H-Index: 6
#2Todd Jenkins (AFRL: Air Force Research Laboratory)H-Index: 1
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As research and development (R&D) in autonomous systems progresses further, more interdisciplinary knowledge is needed from domains as diverse as artificial intelligence (AI), bi-ology, psychology, modeling and simulation (M&S), and robotics. Such R&D efforts are necessarily interdisciplinary in nature and require technical as well as further soft skills of teamwork, communication and integration. In this paper, we introduce a 14 week, summer long internship for developing these skills in underg...
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#1Trevor J. Bihl (AFRL: Air Force Research Laboratory)H-Index: 6
Last. Timothy Machin (AFIT: Air Force Institute of Technology)
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This paper presents a vision of planners, particularly for UAVs, from both an architectural and algorithmic perspective. It reviews key approaches and develops a taxonomy of planning methods. This paper explores various differences and similarities. A technical baseline is developed throughout this process to highlight current research interests, demand signals, and possible gaps in the research. Descriptions of the fundamental issues and limitations of present methods are also included. A commo...
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