Zobrazeno 1 - 10
of 37
pro vyhledávání: '"M. Hussain"'
Autor:
Malek G. M. Hussain
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 58:4875-4890
Multiple-input-multiple-output (MIMO)-radar systems employing ultrawideband (UWB) signals promise enhanced imaging performance. In this article, the generalized ambiguity function (GAF) for an MIMO-radar system is derived by using a set of quasi-orth
Publikováno v:
IET Communications. 14:1543-1553
This paper presents a detailed study of multiple access ultrawideband communications based on M-ary frequency-shift keying modulation of impulse-like carrier waveforms. The proposed signal model is described using expressions of duty cycle, energy, a
Autor:
Haneen H. Alwan, Zahir M. Hussain
Publikováno v:
Journal of Computer Science. 15:1461-1489
In a recent work, chaos has been utilized to modify addresses of message bits while hidden in a cover image. In this study, we extend the above technique to include multiple chaotic maps for increased security. Three systems have been modified using
Autor:
Nashaat M. Hussain Hassan
Publikováno v:
Multidimensional Systems and Signal Processing. 31:591-617
Development of medical image segmentation techniques has become one of the most important challenges in many applications that employ computers-based medical image analysis techniques. However, most of current-existing medical image segmentation tech
Publikováno v:
Micro
Volume 1
Issue 1
Pages 4-42
Volume 1
Issue 1
Pages 4-42
Niobium-doped nanocrystalline Li4Ti5O12 (LTO) is synthesized by the solid-state reaction method, and the influence of dopant concentration (x = 2–10 mol%) on microstructural and electrochemical properties is studied. The X-ray diffraction and Raman
Publikováno v:
Materials Today: Proceedings.
At the present, many medical and military institutions need to transmit data reliably and accurately; thus, any impact on the signal leads to a change of information and affects the patient’s life at the health level or confidential information in
Autor:
Deeksha Devendra, Ruthwik Muppala, Aftab M. Hussain, Eustachio Roberto Matera, Nicola Accettura, Abhinav Navnit
Publikováno v:
ICL-GNSS
2021 International Conference on Localization and GNSS (ICL-GNSS)
International Conference on Localization and GNSS (ICL-GNSS 2021)
International Conference on Localization and GNSS (ICL-GNSS 2021), Jun 2021, Tampere (virtual), Finland. ⟨10.1109/ICL-GNSS51451.2021.9452311⟩
2021 International Conference on Localization and GNSS (ICL-GNSS)
International Conference on Localization and GNSS (ICL-GNSS 2021)
International Conference on Localization and GNSS (ICL-GNSS 2021), Jun 2021, Tampere (virtual), Finland. ⟨10.1109/ICL-GNSS51451.2021.9452311⟩
International audience; The growing need for localization has created an array of alternative approaches to GNSS, based on Wi-Fi, Bluetooth, Ultra-Wideband, etc. Long Range Wide Area Network (LoRaWAN) is one such technology that has garnered tremendo
Autor:
Nuha A. S. Alwan, Zahir M. Hussain
Publikováno v:
Electronics
Volume 10
Issue 11
Electronics, Vol 10, Iss 1245, p 1245 (2021)
Volume 10
Issue 11
Electronics, Vol 10, Iss 1245, p 1245 (2021)
Training data for a deep learning (DL) neural network (NN) controller are obtained from the input and output signals of a conventional digital controller that is designed to provide the suitable control signal to a specified plant within a feedback d
Publikováno v:
2021 6th International Conference for Convergence in Technology (I2CT).
The advent of Internet of Things has resulted in new communication protocols such as LoRaWAN and Narrowband IoT slowly rising to be viable and even better alternatives to traditional protocols such as Wi-Fi and Bluetooth. LoRa in particular, has attr
Autor:
Hind R. Almayyali, Zahir M. Hussain
Publikováno v:
Sensors (Basel, Switzerland)
Sensors
Volume 21
Issue 8
Sensors, Vol 21, Iss 2729, p 2729 (2021)
Sensors
Volume 21
Issue 8
Sensors, Vol 21, Iss 2729, p 2729 (2021)
Despite the increasing role of machine learning in various fields, very few works considered artificial intelligence for frequency estimation (FE). This work presents comprehensive analysis of a deep-learning (DL) approach for frequency estimation of