Results 11 to 20 of about 22,252,197 (309)
The Lossless Adaptive Binomial Data Compression Method
Applied Sciences, 2022 In this paper, we propose a new method for the binomial adaptive compression of binary sequences of finite length without loss of information. The advantage of the proposed binomial adaptive compression method compared with the binomial compression ...
Oleksiy Borysenko +4 more
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Fault Diagnosis of a Propeller Using Sub-Nyquist Sampling and Compressed Sensing
IEEE Access, 2022 The fault diagnosis of rotating machinery is generally performed using methods that employ vibration and sound. These methods are simple and accurate. However, all of these methods measure vibration data on the basis of the sampling theorem.
Yuki Kato
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Efficient data compression in perception and perceptual memory.
Psychology Review, 2020 Efficient data compression is essential for capacity-limited systems, such as biological perception and perceptual memory. We hypothesize that the need for efficient compression shapes biological systems in many of the same ways that it shapes engineered
Christopher Bates, R. Jacobs
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Full-State Quantum Circuit Simulation by Using Data Compression [PDF]
International Conference for High Performance Computing, Networking, Storage and Analysis, 2019 Quantum circuit simulations are critical for evaluating quantum algorithms and machines. However, the number of state amplitudes required for full simulation increases exponentially with the number of qubits.
Xin-Chuan Wu +6 more
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Stochastic Controlled Averaging for Federated Learning with Communication Compression [PDF]
International Conference on Learning Representations, 2023 Communication compression, a technique aiming to reduce the information volume to be transmitted over the air, has gained great interests in Federated Learning (FL) for the potential of alleviating its communication overhead.
Xinmeng Huang, Ping Li, Xiaoyun Li
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Time-Universal Data Compression
Algorithms, 2019 Nowadays, a variety of data-compressors (or archivers) is available, each of which has its merits, and it is impossible to single out the best ones. Thus, one faces the problem of choosing the best method to compress a given file, and this problem is ...
Boris Ryabko
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Interactive Compression of Digital Data
Algorithms, 2010 If we can use previous knowledge of the source (or the knowledge of a source that is correlated to the one we want to compress) to exploit the compression process then we can have significant gains in compression.
Bruno Carpentieri
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Deep learning for in situ data compression of large turbulent flow simulations
, 2020 Large turbulent flow simulations can lead to information bottlenecks as data is generated faster than it can be processed and saved. Innovative in-situ data compression techniques are needed.
Andrew Glaws, R. King, M. Sprague
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Massive optimal data compression and density estimation for scalable, likelihood-free inference in cosmology [PDF]
, 2018 Many statistical models in cosmology can be simulated forwards but have intractable likelihood functions. Likelihood-free inference methods allow us to perform Bayesian inference from these models using only forward simulations, free from any likelihood ...
J. Alsing +2 more
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IEEE Journal of Translational Engineering in Health and Medicine, 2020 Background: The enhancement in the performance of the myoelectric pattern recognition techniques based on deep learning algorithm possess computationally expensive and exhibit extensive memory behavior.
Arvind Gautam +6 more
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