Results 11 to 20 of about 531,033 (266)
Source Coding with a Causal Helper
Information, 2020 A multi-terminal network, in which an encoder is assisted by a side-information-aided helper, describes a memoryless identically distributed source to a receiver, is considered. The encoder provides a non-causal one-shot description of the source to both
Shraga I. Bross
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IEEE Open Journal of the Communications Society, 2022 A major bottleneck in distributed learning is the communication overhead of exchanging intermediate model update parameters between the worker nodes and the parameter server.
Naifu Zhang, Meixia Tao
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Hyperspectral Pansharpening Based on Homomorphic Filtering and Weighted Tensor Matrix
Remote Sensing, 2019 Hyperspectral pansharpening is an effective technique to obtain a high spatial resolution hyperspectral (HS) image. In this paper, a new hyperspectral pansharpening algorithm based on homomorphic filtering and weighted tensor matrix (HFWT) is proposed ...
Jiahui Qu +4 more
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Structure Tensor-Based Algorithm for Hyperspectral and Panchromatic Images Fusion
Remote Sensing, 2018 Restricted by technical and budget constraints, hyperspectral (HS) image which contains abundant spectral information generally has low spatial resolution. Fusion of hyperspectral and panchromatic (PAN) images can merge spectral information of the former
Jiahui Qu +5 more
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On Linear Coding over Finite Rings and Applications to Computing
Entropy, 2017 This paper presents a coding theorem for linear coding over finite rings, in the setting of the Slepian–Wolf source coding problem. This theorem covers corresponding achievability theorems of Elias (IRE Conv. Rec. 1955, 3, 37–46) and Csiszár (IEEE Trans.
Sheng Huang, Mikael Skoglund
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Proceedings of the ACM on Programming Languages, 2017 In this paper, we consider the problem of source code abridgment, where the goal is to remove statements from a source code in order to display the source code in a small space, while at the same time leaving the ``important'' parts of the source code intact, so that an engineer can read the code and quickly understand purpose of the code. To this end,
Binhang Yuan +2 more
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Robust 2-bit Quantization of Weights in Neural Network Modeled by Laplacian Distribution
Advances in Electrical and Computer Engineering, 2021 Significant efforts are constantly involved in finding manners to decrease the number of bits required for quantization of neural network parameters. Although in addition to compression, in neural networks, the application of quantizer models that are ...
PERIC, Z. +3 more
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LDGM Codes for Channel Coding and Joint Source-Channel Coding of Correlated Sources
EURASIP Journal on Advances in Signal Processing, 2005 Summary: We propose a coding scheme based on the use of systematic linear codes with low-density generator matrix (LDGM codes) for channel coding and joint source-channel coding of multiterminal correlated binary sources. In both cases, the structures of the LDGM encoder and decoder are shown, and a concatenated scheme aimed at reducing the error floor
Wei Zhong, Javier Garcia-Frías
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Efficient and Compact Representations of Deep Neural Networks via Entropy Coding
IEEE Access, 2023 Matrix operations are nowadays central in many Machine Learning techniques, including in particular Deep Neural Networks (DNNs), whose core of any inference is represented by a sequence of dot product operations.
Giosue Cataldo Marino +3 more
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Channel Coding and Source Coding With Increased Partial Side Information
Entropy, 2017 Let ( S 1 , i , S 2 , i ) ∼ i . i . d p ( s 1 , s 2 ) , i = 1 , 2 , ⋯ be a memoryless, correlated partial side information sequence. In this work, we study channel coding and source coding problems where the partial side
Avihay Sadeh-Shirazi +2 more
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