This paper provides an adaptation algorithm for the control of complex system via recurrent neural networks. The proposed method is derived from RTRL algorithm. Neural emulator and neural controller parameters are one...
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ISBN:
(纸本)9781424481545
This paper provides an adaptation algorithm for the control of complex system via recurrent neural networks. The proposed method is derived from RTRL algorithm. Neural emulator and neural controller parameters are one-line updated independently. To illustrate the tracking and the disturbance rejection capabilities of the real time control algorithm and the efficiency of the networks parameters relaxation, an application to the large scale process: Tennessee Eastman Challenge Process (TECP) is presented.
A new adaptation algorithm is proposed for adaptive systems with reference model operating independently from the intensity and spectral composition of the input actions and from the range and the rate of variations o...
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HTTP-based Adaptive Streaming (HAS) is the dominant Internet video streaming application. One specific HAS approach, Dynamic Adaptive Streaming over HTTP (DASH), is of particular interest, as it is a widely deployed, ...
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HTTP-based Adaptive Streaming (HAS) is the dominant Internet video streaming application. One specific HAS approach, Dynamic Adaptive Streaming over HTTP (DASH), is of particular interest, as it is a widely deployed, standardized implementation. Prior academic research has focused on networking and protocol issues, and has contributed an accepted understanding of the performance and possible performance issues in large deployment scenarios. Our work extends the current understanding of HAS by focusing directly on the impacts of choice of the video quality adaptation algorithm on end-user perceived quality. In congested network scenarios, the details of the adaptation algorithm determine the amount of bandwidth consumed by the application as well as the quality of the rendered video stream. HAS will lead to user-perceived changes in video quality due to intentional changes in quality video segments, or unintentional perceived quality impairments caused by video decoder artifacts such as pixelation, stutters, or short or long stalls in the rendered video when the playback buffer becomes empty. The HAS adaptation algorithm attempts to find the optimal solution to mitigate the conflict between avoiding buffer stalls and maximizing video quality. In this article, we present results from a user study that was designed to provide insights into "best practice guidelines" for a HAS adaptation algorithm. Our findings suggest that a buffer-based strategy might provide a better experience under higher network impairment conditions. For the two network scenarios considered, the buffer-based strategy is effective in avoiding stalls but does so at the cost of reduced video quality. However, the buffer-based strategy does yield a lower number of quality switches as a result of infrequent bitrate adaptations. Participants in buffer-based strategy do notice the drop in video quality causing a decrease in perceived QoE, but the perceived levels of video quality, viewer frustration, an
Dynamic Adaptive Streaming over HTTP (DASH) is a popular over-the-top video content distribution technique that adapts the streaming session according to the user's network condition typically in terms of down-lin...
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Dynamic Adaptive Streaming over HTTP (DASH) is a popular over-the-top video content distribution technique that adapts the streaming session according to the user's network condition typically in terms of down-link bandwidth. This video quality adaptation can be achieved by scaling the frame quality, spatial resolution or frame rate. Despite the flexibility on the video quality scaling methods, each of these quality scaling dimensions has varying effects on the Quality of Experience (QoE) for end users. Furthermore, in video streaming, the changes in motion over time along with the scaling method employed have an influence on QoE, hence the need to carefully tailor scaling methods to suit streaming applications and content type. In this work, we investigate an intelligent DASH approach for the latest video coding standard H.265 and propose a heuristic QoE-aware cost-efficient adaptation scheme that does not switch unnecessarily to the highest quality level but rather stays temporarily at an intermediate quality level in certain streaming scenarios. Such an approach achieves a comparable and consistent level of quality under impaired network conditions as commonly found in Internet and mobile networks while reducing bandwidth requirements and quality switching overhead. The rationale is based on our empirical experiments, which show that an increase in bitrate does not necessarily mean noticeable improvement in QoE. Furthermore, our work demonstrates that the Signal-to-Noise Ratio (SNR) and the spatial resolution scalability types are the best fit for our proposed algorithm. Finally, we demonstrate an innovative interaction between quality scaling methods and the polarity of switching operations. The proposed QoE-aware scheme is implemented and empirical results show that it is able to reduce bandwidth requirements by up to 41% whilst achieving equivalent QoE compared with a representative DASH reference implementation.
Abstract A new adaptation algorithm is proposed for adaptive systems with reference model operating independently from the intensity and spectral composition of the input actions and from the range and the rate of var...
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Abstract A new adaptation algorithm is proposed for adaptive systems with reference model operating independently from the intensity and spectral composition of the input actions and from the range and the rate of variations of parametric and coordinate disturbances. The problem of this algorithm realizability is considered. The results of simulation of the 6-order adaptive system are presented.
The following topics are dealt with: adaptation algorithm; multimedia architecture design methodology; power optimization and energy characterization; hardware and interface synthesis; embedded software techniques
ISBN:
(纸本)9780780397835
The following topics are dealt with: adaptation algorithm; multimedia architecture design methodology; power optimization and energy characterization; hardware and interface synthesis; embedded software techniques
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