Zobrazeno 1 - 10
of 28
pro vyhledávání: '"M. Hussain"'
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
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
Autor:
Hind Rustum Mohammed, Zahir M. Hussain
Publikováno v:
Computation, Vol 9, Iss 35, p 35 (2021)
Computation
Volume 9
Issue 3
Computation
Volume 9
Issue 3
Accurate, fast, and automatic detection and classification of animal images is challenging, but it is much needed for many real-life applications. This paper presents a hybrid model of Mamdani Type-2 fuzzy rules and convolutional neural networks (CNN
Publikováno v:
Future Generation Computer Systems. 93:1-17
Over the past few years, there has been growing research interests on vehicular ad hoc networks (VANETs) due to their ease of deployment and the potential support for wide range of applications that can greatly enhance our everyday driving experience
Autor:
Zahir M. Hussain, Nuha A. S. Alwan
Publikováno v:
Wireless Personal Communications. 105:941-950
Compressed sensing by random under-sampling has been recently used in the context of energy-efficient moving-target gradient descent localization in wireless sensor networks. The present work investigates the possibility of using deterministic chaos