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Journal of King Saud University: Computer and Information Sciences, 2021 Explosive growth of data in digital world leads to the requirement of efficient technique to store and transmit data. Due to limited resources, data compression (DC) techniques are proposed to minimize the size of data being stored or communicated. As DC
Uthayakumar Jayasankar +2 more
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Data Compression Algorithms for Wireless Sensor Networks: A Review and Comparison
IEEE Access, 2021 Energy consumption has risen to be a bottleneck in wireless sensor networks. This is caused by the challenges faced by these networks due to their tiny sensor nodes that have limited memory storage, small battery capacity, limited processing capability ...
Keleadile Lucia Ketshabetswe +4 more
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Stream-Based Visually Lossless Data Compression Applying Variable Bit-Length ADPCM Encoding [PDF]
Sensors, 2021 Video applications have become one of the major services in the engineering field, which are implemented by server–client systems connected via the Internet, broadcasting services for mobile devices such as smartphones and surveillance cameras for ...
Shinichi Yamagiwa, Yuma Ichinomiya
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Nine Algorithms That Changed the Future, 2020 2. Saywood’s book, chapter 2, question #4. Suppose we have a source with a probability model P={p0, p1, ..., pm} and entropy HP. Suppose we have another source with probability model Q={q0, q1, ..., qm} and entropy HQ, where qi = pi, i = 0, 1, ..., j-2 ...
semanticscholar +4 more sources
An Introduction to Neural Data Compression [PDF]
Foundations and Trends in Computer Graphics and Vision, 2022 Neural compression is the application of neural networks and other machine learning methods to data compression. Recent advances in statistical machine learning have opened up new possibilities for data compression, allowing compression algorithms to be ...
Yibo Yang, Stephan Mandt, Lucas Theis
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Toward Bayesian Data Compression [PDF]
Annalen der Physik, 2021 AbstractIn order to handle large datasets omnipresent in modern science, efficient compression algorithms are necessary. Here, a Bayesian data compression (BDC) algorithm that adapts to the specific measurement situation is derived in the context of signal reconstruction.
Johannes Harth‐Kitzerow +3 more
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Data compression for quantum machine learning [PDF]
Physical Review Research, 2022 The advent of noisy-intermediate scale quantum computers has introduced the exciting possibility of achieving quantum speedups in machine learning tasks.
R. Dilip +3 more
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Biosignal Compression Toolbox for Digital Biomarker Discovery
Sensors, 2021 A critical challenge to using longitudinal wearable sensor biosignal data for healthcare applications and digital biomarker development is the exacerbation of the healthcare “data deluge,” leading to new data storage and organization challenges and costs.
Brinnae Bent +3 more
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Bicriteria data compression [PDF]
Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms, 2013 The advent of massive datasets (and the consequent design of high-performing distributed storage systems) have reignited the interest of the scientific and engineering community towards the design of lossless data compressors which achieve effective compression ratio and very efficient decompression speed.
FARRUGGIA, ANDREA +3 more
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Universal triple encoding for compression and protecting binary data
Безопасность информационных технологий, 2021 The paper is devoted to the actual problem of compression of processed and transmitted data, as well as of the data storage and protection. The analysis and features of data compression methods are presented.
Victor A. Shurygin, Igor M. Yadykin
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