Image and Video Compression Standards: Algorithms and Architectures
Image and Video Compression Standards: Algorithms and Architectures
Recurrent Neural Networks for Prediction: Learning Algorithms,Architectures and Stability
Recurrent Neural Networks for Prediction: Learning Algorithms,Architectures and Stability
GPRS Congestion Control Algorithm Based on Fuzzy Kernel Neural Networks
ISDA '06 Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications - Volume 01
Neural-based downlink scheduling algorithm for broadband wireless networks
Computer Communications
Network Performance Analysis: Using the J Programming Language
Network Performance Analysis: Using the J Programming Language
Prediction of MPEG-coded video source traffic using recurrent neural networks
IEEE Transactions on Signal Processing
Fuzzy logic = computing with words
IEEE Transactions on Fuzzy Systems
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This paper is concerned with an intelligent application of Moving Picture Expert Group (MPEG) video transmission in a Bluetooth link. MPEG Variable Bit Rate (VBR) video is data hungry and results in excessive data loss and time delay over wireless networks. In a Bluetooth channel transmission rate is unpredictable as result of interferences by channel noises or other close by wireless devices. Therefore, it is difficult to transmit MPEG VBR video in Bluetooth without data loss and/or time delay. A buffer entitled 'traffic regulating buffer' is introduced before the Bluetooth protocol stack to prevent excessive overflow of MPEG video data over the network. Two novel neural fuzzy schemes are presented in this paper to monitor the traffic regulating buffer input and output rates, in order to ensure the video stream conforms to the traffic conditions of Bluetooth. The computer simulation results demonstrate that the two supervised neural fuzzy schemes reduce standard deviation and data loss, when compared with a traditional MPEG VBR video transmission over Bluetooth.