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检索条件"主题词=compression algorithms"

共 2082 条记录，以下是111-120 订阅

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Benchmarking Parallel Electrocardiogram compression Based on Successive Differences

Benchmarking Parallel Electrocardiogram Compression Based on...

引用

Telecommunications Forum (TELFOR)

作者： A. Shekerov V. Zdraveski M. Gusev Faculty of Computer Science and Engineering Ss. Cyril and Methodius University in Skopje Skopje North Macedonia

ISBN: (数字)9798350391060

ISBN: (纸本)9798350391077

We focus on parallelization methods for an electrocardiogram data compression algorithm based on successive differences to gain insights into the advantages and disadvantages of parallel implementations. The experimental methodology exposes a comprehensive and systematic benchmarking process with varying input file sizes, hosting machine characteristics, and two popular parallelization approaches: OpenMP and MPI. We check the research hypothesis to see if parallelizing the compression algorithm can reduce the runtime while keeping the original algorithm’s compression results. Our analysis and discussion show that OpenMP outperforms MPI. An OpenMP implementation with 12 threads on a processor with six cores achieves the highest average speedup of 7 versus a single-thread implementation. Performance gains depend heavily on the utilized hardware and the degree of parallelism.

关键词： Systematics Runtime Data compression Electrocardiography Benchmark testing Performance gain Parallel processing Hardware Telecommunications compression algorithms

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ACD: A Lossless compression Based on Dimensionality Reduction for Multi-dimensional Time Series Data

ACD: A Lossless Compression Based on Dimensionality Reductio...

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Frontiers Technology of Information and Computer (ICFTIC), IEEE International Conference on

作者： Haolong Chen Liang Liu College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (数字)9798331541750

ISBN: (纸本)9798331541767

Multi-dimensional time series data are generated daily in lots of domains. Compressing these data to reduce storage overhead is an important topic. Existing compression algorithms resort to converting multi-dimensional time series data into multiple separate one-dimensional data to compress. However, these algorithms fail to exploit both intra- and inter-correlation among dimensions and the compression is not efficient. To solve the problem, this paper introduces a novel multi-dimensional time series compression framework called ACD, a lossless compression based on dimensionality reduction. Initially, the n-dimensional time series data undergo dimensionality reduction via space-filling curves(SFCs) encoding. Subsequently, we partition the encoded data heuristically into several segments based on distinctive patterns in different time windows. Finally, suitable compression is conducted according to segment patterns. We implement our algorithm in an out-of-box commercial time series database engine VictoriaMetrics. Our experiments demonstrate that ACD achieves at least 40% improvement over existing methods such as Chimp, Gorilla, and DeltaZstd as evaluated through the Time Series Benchmark Suite(TSBS).

关键词： Dimensionality reduction Databases Time series analysis Data compression Adaptive algorithms Benchmark testing Encoding Partitioning algorithms Engines compression algorithms

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Research and Application of LZ-Hf Algorithm in compression of Automotive CAN Message Data

Research and Application of LZ-Hf Algorithm in Compression o...

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Computer Science, Electronic Information Engineering and Intelligent Control Technology (CEI), IEEE International Conference on

作者： Chuanbo Liu Bin Zhu Jun Zhang Tiancheng Jiang College of Mechanical and Electrical Engineering Wuhan University of Technology Wuhan China

ISBN: (数字)9798350378542

ISBN: (纸本)9798350378559

With the increasing richness of the functions carried on top of the car, the amount of data generated on the nodes carried on the vehicle CAN bus is getting bigger and bigger, and it takes more and more time to upload the data of the collected CAN messages to the server side. Aiming at this problem, this paper proposes a LZ-Hf algorithm for message compression by combining the data characteristics of automotive CAN messages, and designs a data acquisition system so as to obtain CAN message data to verify the algorithm. After several tests and analysis of files of different sizes, the algorithm drastically reduces the time needed to upload the data from the TF card to the cloud.

关键词： Computer science Data acquisition Encoding Servers Automobiles compression algorithms Automotive engineering Intelligent control

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A Temporal Data compression Based on Dual Autoregressive Prediction Method

A Temporal Data Compression Based on Dual Autoregressive Pre...

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IEEE International Conference on Electronics and Communication Engineering (ICECE)

作者： YongPan Zhang YuanChen Liu Ping Shen Zheng Zhang Chao Qian Cheng Ding Digital Operations Promotion Department China Telecom Jiangsu branch Nanjing China School of Internet of Things Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (数字)9798331517755

ISBN: (纸本)9798331517762

A temporal data compression method based on rebuilding the predictive model is proposed. This method employs a dual autoregressive prediction model to forecast the temporal data, storing only the residuals between the predicted and actual values, along with the coefficients of the prediction model. During decoding, the prediction model coefficients are used to reconstruct the prediction model to generate predicted values, which are then combined with the residuals to recover the original values. Since the residuals are significantly smaller than the original values, they can be quantized using fewer bits, while the prediction model coefficients, once stored, do not need to be stored repeatedly over *** results on eight real datasets of varying sizes and types demonstrate the excellent compression performance of this method.

关键词： Costs Time series analysis Data compression Predictive models Aerospace electronics Data models Decoding compression algorithms

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A 4K60fps Ultra-Low-Latency Light compression Encoder for Bandwidth-Constrained Scenarios

A 4K60fps Ultra-Low-Latency Light Compression Encoder for Ba...

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International Conference on Solid-State and Integrated Circuit Technology

作者： Yanzhong Li Leilei Huang Yibo Fan State Key Laboratory of Integrated Chips and Systems Fudan University Shanghai China Institute of Microelectronic Circuits and Systems East China Normal University Shanghai China

ISBN: (数字)9798350361834

ISBN: (纸本)9798350361841

Light compression standards are developed for low latency video transmission requirements. However, the compression ratio (CR) of most of the light compression standards is not enough for bandwidth-constrained scenarios. The limited CR leads to an increase in cache, which in turn affects latency and area. In this paper, we address to propose a high efficient light compression algorithm with a CR of 20. We implemented the proposed design on Xilinx ZCU102 FPGA. As a result, the codec system has an end-to-end latency of 250.76us with a 150MHz clock.

关键词： Integrated circuit technology Costs Codecs Encoding Hardware Low latency communication Standards Field programmable gate arrays compression algorithms Clocks

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Next-Generation Sequencing Data compression and Storage Solutions

Next-Generation Sequencing Data Compression and Storage Solu...

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Communication, Computing and Signal Processing (IICCCS), IEEE International Conference on

作者： Sandeep Pandey Jejji Singh Arora Kassem AL-Attabi Ikramova Madina Sunnatilla Qizi G. Sathi Uk Urmila Department of Electrical & Electronics Engineering IES College of Technology Bhopal M.P. India Department of Computer Application Chandigarh Engineering College Chandigarh Group of Colleges Mohali Punjab India Department Of Computers Techniques Engineering College Of Technical Engineering The Islamic University Najaf Iraq Department Of Computers Techniques Engineering College Of Technical Engineering The Islamic University Of Al Diwaniyah Al Diwaniyah Iraq Tashkent Institute of Irrigation and Agricultural Mechanization Engineers" National Research University Tashkent Uzbekistan Prince Shri Venkateshwara Padmavathy Engineering College Chennai India Department of AI & ML Saveetha Institute of Medical and Technical Sciences Chennai Tamilnadu India

ISBN: (数字)9798350390759

ISBN: (纸本)9798350390766

They produce huge amount of data which require efficient compression and management mechanisms hence the need to adopt Next-Generation Sequencing (NGS). In this paper, the performance of different compression algorithms and their implementation with local and cloud-based storage systems are assessed and compared using the lossless and lossy storage efficiency analysis. This study reveals that reference-based compression shows the highest compression ratio on the whole with lossy methods having shorter processing time ahead of other methods. A comparison of the costs shows the feasibility of local and cloud storage options to bear substantial costs. The study further supports that sophisticated algorithms as well as universally recognized formats are crucial for organizing NGS data Stream.

关键词： Cloud computing Sequential analysis Costs Signal processing algorithms Data compression Signal processing Telecommunication computing Reliability Next generation networking compression algorithms

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A Hardware-friendly Image Mapping Parameter Matrix compression Algorithm

A Hardware-friendly Image Mapping Parameter Matrix Compressi...

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IEEE International Conference on Circuits and Systems (ICCS)

作者： Tao Li Zihan Lv Xianyang Jiang School of Physics and Technology Wuhan University Wuhan China

ISBN: (数字)9798350352153

ISBN: (纸本)9798350352160

Image mapping is widely applied in various fields of multi-camera video, panoramic display, medical imaging, and AR augmented reality. Generally speaking, its software implementation is a computing-intensive task and its hardware implementation needs a lot of both hardware computing resources and storage space. In order to attack such disadvantages, an efficient and hardware-friendly image mapping parameter matrix compression algorithm based on bilinear interpolation has been proposed. The proposed algorithm can theoretically achieve compression ratio with any scale and any image size, which largely benefits its circuit acceleration. The proposed algorithm has been evaluated on image quality from both subjective and objective perspectives based on both USIS-D dataset and a self-shot data, meanwhile it has been verified on a Xilinx Kintex7-325T FPGA board. Experimental results demonstrated that the proposed algorithm significantly cuts down computation and storage resource consumption under the premise of losing little image quality.

关键词： Image quality Interpolation Image coding Memory management Software algorithms Hardware Software System-on-chip SDRAM compression algorithms

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Simulation Analysis of CS-ACELP Speech compression Algorithm Based on Mute Detection Technology

Simulation Analysis of CS-ACELP Speech Compression Algorithm...

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Electronic Information Engineering and Computer Science (EIECS), 2021 International Conference on

作者： Bo Zhou Zhaoyang Li Zongju Xiong Wanbin Zhang Communication Systems Department Xichang Satellite Launch Center of China Xichang Sichuan China

ISBN: (数字)9798331531409

ISBN: (纸本)9798331531416

Based on the study of CS-ACELP speech compression algorithm and mute detection technology, we propose a new mute detection scheme. Based on short-time average amplitude and short-term average over zero rate, it distinguishes noise, clearing and turbidity through the two-level judgment method. Through simulation analysis, the algorithm is based on CS-ACELP algorithm proposed G.729B, it reduces the complexity and achieves the effect of reducing the code rate.

关键词： Resistance Computer science Codes Turbidity Real-time systems Encoding Complexity theory Detection algorithms compression algorithms Signal to noise ratio

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Efficient Data compression based on Run-length Coding for Electronic Skins

Efficient Data Compression based on Run-length Coding for El...

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International Conference on Communication Technology (ICCT)

作者： Wei Yao Shengliang Peng Libo Chen Zhi-Bin Zhang College of Information Science and Engineering Huaqiao University Xiamen China Department of Electrical Engineering Division of Solid-State Electronics Uppsala University Uppsala Sweden

ISBN: (数字)9798350363760

ISBN: (纸本)9798350363777

Electronic skin (E-skin) is an advanced wearable technique with great potential in tactile feedback applications. E-skins with a large number of sensors may generate a great amount of data that usually incurs serious difficulties in data processing and transmission. Current research on E-skins mainly focuses on hardware design and sensor development, without considering the issue of data compression. To address the issue, this paper reports efficient compression of data from neuromorphic E-skin using algorithms based on run-length coding. Two run-of-zero-based coding methods, including Golomb coding and frequency-directed run-length (FDR) coding, are exploited to achieve data compression. Experimental results show that both the Golomb coding and FDR coding based algorithms can compress the E-skin data efficiently with compression ratios over 79%.

关键词： Electric potential Electronic skin Neuromorphics Data compression Tactile sensors Data processing Encoding Hardware Sensors compression algorithms

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An Enhanced Text compression Approach Using Transformer-based Language Models

An Enhanced Text Compression Approach Using Transformer-base...

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IEEE Region 10 Symposium

作者： Chowdhury Mofizur Rahman Mahbub E Sobhani Anika Tasnim Rodela Swakkhar Shatabda Department of Computer Science and Engineering State University of Bangladesh Department of Computer Science and Engineering United International University Department of Computer Science and Engineering BRAC University

ISBN: (数字)9798350364866

ISBN: (纸本)9798350364873

Text compression shrinks textual data while keeping crucial information, eradicating constraints on storage, band-width, and computational efficacy. The integration of lossless compression techniques with transformer-based text decompression has received negligible attention, despite the increasing volume of English text data in communication. The primary barrier in advancing text compression and restoration involves optimizing transformer-based approaches with efficient pre-processing and integrating lossless compression algorithms, that remained unresolved in the prior attempts. Here, we propose a transformer-based method named RejuvenateFormer for text decompression, addressing prior issues by harnessing a new pre-processing technique and a lossless compression method. Our meticulous pre-processing technique incorporating the Lempel-Ziv-Welch algorithm achieves compression ratios of 12.57, 13.38, and 11.42 on the BookCorpus, EN-DE, and EN-FR corpora, thus showing state-of-the-art compression ratios compared to other deep learning and traditional approaches. Furthermore, the RejuvenateFormer achieves a BLEU score of 27.31, 25.78, and 50.45 on the EN-DE, EN-FR, and BookCorpus corpora, showcasing its comprehensive efficacy. In contrast, the pre-trained T5-Small exhibits better performance over prior state-of-the-art models.

关键词： Training Deep learning Attention mechanisms Computer architecture Linguistics Transformers Encoding compression algorithms IEEE Regions

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