MPEG Handbook
Image and Video Compression Standards: Algorithms and Architectures
Image and Video Compression Standards: Algorithms and Architectures
Artificial Intelligence: A Guide to Intelligent Systems
Artificial Intelligence: A Guide to Intelligent Systems
EURASIP Journal on Wireless Communications and Networking
Short-term MPEG-4 video traffic prediction using ANFIS
International Journal of Network Management
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Delay Constrained Fuzzy Rate Control for Video Streaming over DVB-H
IIH-MSP '06 Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia
Is there a need for fuzzy logic?
Information Sciences: an International Journal
ZigBee Wireless Networks and Transceivers
ZigBee Wireless Networks and Transceivers
A fuzzy control scheme for video transmission in Bluetooth wireless
Information Sciences: an International Journal
ZigBee Wireless Sensor and Control Network
ZigBee Wireless Sensor and Control Network
A qoe fuzzy routing protocol for wireless mesh networks
FMN'10 Proceedings of the Third international conference on Future Multimedia Networking
A study of real-time packet video quality using random neural networks
IEEE Transactions on Circuits and Systems for Video Technology
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This research paper presents Neuro-Fuzzy applications to Moving Picture Expert Group (MPEG-4) video transmission in IEEE 802.15.4 ZigBee wireless. ZigBee can operate within 2.4GHz frequency with a data rate of 250kb/s, which may interfere with other wireless devices functioning within the same frequency band such as WiFi and Bluetooth. MPEG-4 Variable Bit Rate (VBR) video demands large bandwidth, and may cause data loss and time delay in the data rate limited ZigBee channel as a result of high variation in bit rate. Consequently, it is almost impracticable for MPEG-4 VBR video to be transmitted in the ZigBee channel. This paper introduces two new Neuro-Fuzzy schemes to monitor the input and the output of a data storage entitled traffic-regulating buffer. The input of the buffer is controlled by a Neuro-Fuzzy scheme to ensure that the traffic-regulating buffer neither flooded nor starved with video data. The output of the traffic-regulating buffer is observed by a second Neuro-Fuzzy scheme to make sure the departure-rate conforms to the traffic condition of ZigBee. The simulation results demonstrate that the proposed two Neuro-Fuzzy schemes reduce the excessive data loss and improve the picture quality, as compared with the conventional MPEG-4 VBR video over ZigBee.