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السجلات المعروضة 11 -- 20 من 103
A cooperative Q-learning approach for online power allocation in femtocell networks
(
IEEE
, 2013 , Conference Paper)
In this paper, we address the problem of distributed interference management of cognitive femtocells that share the same frequency range with macrocells using distributed multiagent Q-learning. We formulate and solve three ...
Adaptive compression and optimization for real-time energy-efficient wireless EEG monitoring systems
(
IEEE
, 2013 , Conference Paper)
Recent technological advances in wireless body sensor networks (WBSN) have made it possible for the development of innovative medical applications to improve health care and the quality of life. Electroencephalography ...
Optimal cooperative cognitive relaying and spectrum access for an energy harvesting cognitive radio: Reinforcement learning approach
(
Institute of Electrical and Electronics Engineers Inc.
, 2015 , Conference Paper)
In this paper, we consider a cognitive setting under the context of cooperative communications, where the cognitive radio (CR) user is assumed to be a self-organized relay for the network. The CR user and the primary user ...
Evidence theory-based approach for epileptic seizure detection using EEG signals
(
IEEE
, 2012 , Conference Paper)
Electroencephalogram (EEG) is one of the potential physiological signals used for detecting epileptic seizure. Discriminant features, representing different brain conditions, are often extracted for diagnosis purposes. ...
Distributed interference management using Q-Learning in cognitive femtocell networks: New USRP-based implementation
(
Institute of Electrical and Electronics Engineers Inc.
, 2015 , Conference Paper)
Femtocell networks have become a promising solution in supporting high data rates for 5G systems, where cell densification is performed using the small femtocells. However, femtocell networks have many challenges. One of ...
Design and analysis of an adaptive compressive sensing architecture for epileptic seizure detection
(
IEEE Computer Society
, 2013 , Conference Paper)
Epileptic detection techniques rely heavily on the Electroencephalography (EEG) as a representative signal carrying valuable information pertaining to the current brain state. In this work, we investigate the stability of ...
DistPrivacy: Privacy-Aware Distributed Deep Neural Networks in IoT surveillance systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
With the emergence of smart cities, Internet of Things (IoT) devices as well as deep learning technologies have witnessed an increasing adoption. To support the requirements of such paradigm in terms of memory and computation, ...
Non-data-aided SNR estimation for QPSK modulation in AWGN channel
(
IEEE Computer Society
, 2014 , Conference Paper)
Signal-to-noise ratio (SNR) estimation is an important parameter that is required in any receiver or communication systems. It can be computed either by a pilot signal data-aided approach in which the transmitted signal ...
Effective seizure detection through the fusion of single-feature enhanced-k-NN classifiers of EEG signals
(
IEEE
, 2013 , Conference Paper)
Electroencephalogram (EEG) physiological signals are widely used for detecting epileptic seizure. To reduce complexity stemming from the dimensionality problem, EEG signals are often reduced into a smaller set of discriminant ...
Performance analysis for truncated ARQ based DSFBC-CO-OFDM communication scheme
(
IEEE
, 2011 , Conference Paper)
We develop and analyze an ARQ (Automatic Repeat reQuest) based distributed space-frequency block code-orthogonal frequency division multiplexing protocol for cooperative communications (DSFBC-CO-OFDM). At PHY layer, space ...