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NYI: Dedicated VLSI Digital Signal and Image Processors

NYI: Dedicated VLSI Digital Signal and Image Processors
NYI:专用 VLSI 数字信号和图像处理器
批准号:
9258670
负责人:
Keshab Parhi
金额:
$31.25万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
1992
资助国家:
美国
项目状态:
已结题
起止时间:
1992-09-15 至 1998-10-31

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中文摘要
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英文摘要
Parhi Research efforts are directed towards the design of dedicated, high-performance digital signal and image processors. The emphasis is on real-time processing, where samples are processed as they are received from the source, as opposed to being stored in buffers and then processed in batch. Design of algorithm topologies for recursive signal processing algorithms were once considered a major challenge. Using the relaxed look-ahead technique, new concurrent algorithms and topologies for adaptive LMS and lattice filters, cascade and lattice recursive digital filters, and predictive speech and image coders have been developed. Design of concurrent topologies for wave digital filters, decision-feedback equalizers, and adaptive differential vector quantizers are being pursued. The decoding speed in Huffman and arithmetic coders (used for lossless compression) is limited due to the feedback. For the Huffman decoder, the codeword length multiplicity constraint is being exploited to design codes where multiple bits can be simultaneously decoded in parallel. The performance of these decoders is further improved by the use of conditional coding. Novel approaches for design of parallel arithmetic coders are also being pursued.
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Collaborative Research: SHF: Small: Efficient and Scalable Privacy-Preserving Neural Network Inference based on Ciphertext-Ciphertext Fully Homomorphic Encryption
  • 批准号:
    2243053
  • 项目类别:
    Standard Grant
  • 资助金额:
    $32.5万
  • 财政年份:
    2023
  • 负责人:
    Keshab Parhi
  • 依托单位:
Collaborative Research: SHF: Medium: TensorNN: An Algorithm and Hardware Co-design Framework for On-device Deep Neural Network Learning using Low-rank Tensors
  • 批准号:
    1954749
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $40.0万
  • 财政年份:
    2020
  • 负责人:
    Keshab Parhi
  • 依托单位:
SHF: Small: Collaborative Research: LDPD-Net: A Framework for Accelerated Architectures for Low-Density Permuted-Diagonal Deep Neural Networks
  • 批准号:
    1814759
  • 项目类别:
    Standard Grant
  • 资助金额:
    $27.5万
  • 财政年份:
    2018
  • 负责人:
    Keshab Parhi
  • 依托单位:
EAGER: Low-Energy Architectures for Machine Learning
  • 批准号:
    1749494
  • 项目类别:
    Standard Grant
  • 资助金额:
    $12.5万
  • 财政年份:
    2017
  • 负责人:
    Keshab Parhi
  • 依托单位:
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