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Complexity Optimization Strategies for Adaptive Multimedia Receivers

Complexity Optimization Strategies for Adaptive Multimedia Receivers
自适应多媒体接收器的复杂度优化策略
批准号:
0541453
负责人:
Mihaela van der Schaar
金额:
$49.96万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2006
资助国家:
美国
项目状态:
已结题
起止时间:
2006-04-15 至 2010-03-31

项目摘要

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中文摘要
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英文摘要
This project is premised on the belief that a fundamentally different approach is necessary for designing and implementing multimedia compression, protection and transmission algorithms and systems for resource-constrained networked devices. The main idea is that instead of considering multimedia algorithms as a given and adapting the implementations reactively to match the requirements of these algorithms, proactive joint optimization of the algorithms, their parameters, and the implementation task partitioning is performed. The system is therefore able to maintain operation at a point in rate-distortion-complexity space in accordance with a constellation of factors and constraints including distortion tolerance, power, platform architecture characteristics, network behavior, and critically, data attributes. A global optimization framework and associated algorithms that consider the data-specific impact on the system factors listed above, allowing cost functions describing these tradeoffs to be formally described and then optimized as appropriate to different devices, networks and applications will be developed. Specifically: 1) complexity description methods and models, 2) data-aware channel decoding methods that combine feedback from the decoder and system knowledge to adapt the processing, 3) joint source-channel coding methods that exploit error concealment in combination with knowledge of the time- and content-varying sensitivity of multimedia data to errors, and 4) optimized resource management. The broader impact of the project is in the area of educating next generation students and industry partners in optimized resource-aware system design. Developing formal methods, algorithms and models will lead to improved multimedia performance over existing resource-constrained systems and also provide valuable insights into the design of next generation multimedia compression algorithms that should be complexity scalable, as well as system designs that should be multimedia aware.
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CIF: Small: Networks: Evolution, Learning and Social Norms
  • 批准号:
    1524417
  • 项目类别:
    Standard Grant
  • 资助金额:
    $48.26万
  • 财政年份:
    2015
  • 负责人:
    Mihaela van der Schaar
  • 依托单位:
EAGER-DynamicData: Real-time Discovery and Timely Event Detection from Dynamic and Multi-Modal Data Streams
  • 批准号:
    1462245
  • 项目类别:
    Standard Grant
  • 资助金额:
    $26.68万
  • 财政年份:
    2015
  • 负责人:
    Mihaela van der Schaar
  • 依托单位:
Planning Grant: I/UCRC for Semantic Computing
  • 批准号:
    1338935
  • 项目类别:
    Standard Grant
  • 资助金额:
    $1.15万
  • 财政年份:
    2013
  • 负责人:
    Mihaela van der Schaar
  • 依托单位:
CIF: Small: Intervention: A Design Framework for Resource Sharing and Exchanges Among Self-interested Users
  • 批准号:
    1218136
  • 项目类别:
    Standard Grant
  • 资助金额:
    $49.17万
  • 财政年份:
    2012
  • 负责人:
    Mihaela van der Schaar
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
供应链管理中的稳健型(Robust)策略分析和稳健型优化(Robust Optimization )方法研究
  • 批准号:
    70601028
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    7.0万元
  • 批准年份:
    2006
  • 负责人:
    王明征
  • 依托单位: