NDLI: Application of neural-fuzzy controller for streaming video over Bluetooth 1.2

Content Provider	Springer Nature Link
Author	Remy, Guillaume F. Kazemian, Hassan B. Picton, Phil
Copyright Year	2010
Abstract	This paper is to introduce an application of Computational Intelligence (CI) to Moving Picture Expert Group-4 (MPEG-4) video compression over IEEE.802.15.1 wireless communication, known as Bluetooth 1.2, in order to improve picture quality. The 2.4 GHz Industrial, Scientific and Medical frequency band is used for the IEEE.802.15.1 standard. IEEE.802.15.1 can be affected by noise and interference due to other neighboring wireless devices sharing the same frequency carrier. The noise and interference create difficulties in ascertaining an accurate real-time transmission rate at the receiving end. Furthermore, the MPEG-4 codec is an object-oriented compression system and demands a high bandwidth. It is therefore difficult to avoid excessive delay, image quality degradation and/or data loss during MPEG-4 video transmission over standard systems. A new buffer entitled ‘buffer added’ has been introduced at the input of the Bluetooth 1.2 device. This buffer is controlled by a Rule-Based Fuzzy (RBF) logic controller at the input and a neural-fuzzy controller (NFC) at the output. The two new fuzzy rules manipulate and supervise the flow of video over the Bluetooth 1.2 standard. The computer simulation results illustrate the comparison between a non-CI video transmission over Bluetooth 1.2 and the proposed design, confirming that the applications of RBF and NFC do improve the image quality, reduce data loss and reduce time delay.
Starting Page	879
Ending Page	887
Page Count	9
File Format	PDF
ISSN	09410643
Journal	Neural Computing and Applications
Volume Number	20
Issue Number	6
e-ISSN	14333058
Language	English
Publisher	Springer-Verlag
Publisher Date	2010-12-04
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Bluetooth 1.2 Neural-fuzzy control Rule-based fuzzy MPEG-4 video Simulation and Modeling
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Software

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