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Articles 1 - 5 of 5
Full-Text Articles in Physics
Chaotic Phase-Coded Waveforms With Space-Time Complementary Coding For Mimo Radar Applications, Sheng Hong, Fuhui Zhou, Yantao Dong, Zhixin Zhao, Yuhao Wang, Maosong Yan
Chaotic Phase-Coded Waveforms With Space-Time Complementary Coding For Mimo Radar Applications, Sheng Hong, Fuhui Zhou, Yantao Dong, Zhixin Zhao, Yuhao Wang, Maosong Yan
Electrical and Computer Engineering Faculty Publications
A framework for designing orthogonal chaotic phase-coded waveforms with space-time complementary coding (STCC) is proposed for multiple-input multiple-output (MIMO) radar applications. The phase-coded waveform set to be transmitted is generated with an arbitrary family size and an arbitrary code length by using chaotic sequences. Due to the properties of chaos, this chaotic waveform set has many advantages in performance, such as anti-interference and low probability of intercept. However, it cannot be directly exploited due to the high range sidelobes, mutual interferences, and Doppler intolerance. In order to widely implement it in practice, we optimize the chaotic phase-coded waveform set from …
Rotation Of Two-Petal Laser Beams In The Near Field Of A Spiral Microaxicon, S. S. Stafeev, Liam O'Faolain, M. V. Kotlyar
Rotation Of Two-Petal Laser Beams In The Near Field Of A Spiral Microaxicon, S. S. Stafeev, Liam O'Faolain, M. V. Kotlyar
Cappa Publications
Using a spiral microaxicon with the topological charge 2 and NA = 0.6 operating at a 532-nm wavelength and fabricated by electron-beam lithography, we experimentally demonstrate the rotation of a two-petal laser beam in the near field (several micrometers away from the axicon surface). The estimated rotation rate is 55 °/mm and linearly dependent on the on-axis distance, with the theoretical rotation rate being 53 °/mm. The experimentally measured rotation rate is found to be linear and coincident with the simulation results only on the on-axis segment from 1.5 to 3 mm. The experimentally measured rotation rate is 66 °/mm …
Enabling Autonomous Navigation For Affordable Scooters, Kaikai Liu, Rajathswaroop Mulky
Enabling Autonomous Navigation For Affordable Scooters, Kaikai Liu, Rajathswaroop Mulky
Faculty Publications
Despite the technical success of existing assistive technologies, for example, electric wheelchairs and scooters, they are still far from effective enough in helping those in need navigate to their destinations in a hassle-free manner. In this paper, we propose to improve the safety and autonomy of navigation by designing a cutting-edge autonomous scooter, thus allowing people with mobility challenges to ambulate independently and safely in possibly unfamiliar surroundings. We focus on indoor navigation scenarios for the autonomous scooter where the current location, maps, and nearby obstacles are unknown. To achieve semi-LiDAR functionality, we leverage the gyros-based pose data to compensate …
Handwritten Bangla Character Recognition Using The State-Of-The-Art Deep Convolutional Neural Networks, Md Zahangir Alom, Paheding Sidike, Mahmudul Hasan, Tarek M. Taha, Vijayan K. Asari
Handwritten Bangla Character Recognition Using The State-Of-The-Art Deep Convolutional Neural Networks, Md Zahangir Alom, Paheding Sidike, Mahmudul Hasan, Tarek M. Taha, Vijayan K. Asari
Electrical and Computer Engineering Faculty Publications
In spite of advances in object recognition technology, handwritten Bangla character recognition (HBCR) remains largely unsolved due to the presence of many ambiguous handwritten characters and excessively cursive Bangla handwritings. Even many advanced existing methods do not lead to satisfactory performance in practice that related to HBCR. In this paper, a set of the state-of-the-art deep convolutional neural networks (DCNNs) is discussed and their performance on the application of HBCR is systematically evaluated. The main advantage of DCNN approaches is that they can extract discriminative features from raw data and represent them with a high degree of invariance to object …
Datanet: Deep Learning Based Encrypted Network Traffic Classification In Sdn Home Gateway, Pan Wang, Feng Ye, Xuejiao Chen, And Yi Qian
Datanet: Deep Learning Based Encrypted Network Traffic Classification In Sdn Home Gateway, Pan Wang, Feng Ye, Xuejiao Chen, And Yi Qian
Electrical and Computer Engineering Faculty Publications
A smart home network will support various smart devices and applications, e.g., home automation devices, E-health devices, regular computing devices, and so on. Most devices in a smart home access the Internet through a home gateway (HGW). In this paper, we propose a software-defined- network (SDN)-HGW framework to better manage distributed smart home networks and support the SDN controller of the core network. The SDN controller enables efficient network quality-of-service management based on real-time traffic monitoring and resource allocation of the core network. However, it cannot provide network management in distributed smart homes. Our proposed SDN-HGW extends the control to …