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data compression method based on information preservation for wideband radar LFM signal echo

JOURNAL OF ENGINEERING-JOE 2019年第21期2019卷 7568-7572页

作者： Gao, Lei Zeng, Yong-hu Wang, Lian-dong Wang, Wei State Key Lab Complex Electromagnet Environm Effe Luoyang 471003 Peoples R China Natl Univ Def Technol Coll Elect Sci Changsha 410073 Hunan Peoples R China

With the increase of radar signal bandwidth and the application of RF directing sampling technology, wideband radars are facing greater pressures for data transmission, storage, and processing. Based on the relationship between linear frequency modulation (LFM for short) signal and LFM-stepped signal, synthesis method of high-resolution range profile (HRRP for short) for LFM step signal can be applied to LFM signal. Combining the synthesis method of HRRP for LFM signal with compressed sensing theory, this study proposes a new compression method for wideband radar echo with LFM signal style based on random segment selection and analyses the constraint conditions of the proposed data compression method. Finally, the validity and practicability of the proposed data compression method are verified from two aspects: simulation experiment and actual data processing.

关键词： radar signal processing radar resolution echo data compression radar target recognition compressed sensing frequency modulation radar imaging radar detection data compression method wideband radar LFM signal echo radar signal bandwidth wideband radars data transmission LFM-stepped signal synthesis method high-resolution range profile LFM step signal compressed sensing theory wideband radar echo LFM signal style actual data processing

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Compressing three-dimensional sparse arrays using inter- and intra-task parallelization strategies on Intel Xeon and Xeon Phi

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JOURNAL OF SUPERCOMPUTING 2017年第8期73卷 3391-3410页

作者： Lin, Chun-Yuan Yen, Huang Ting Hung, Che-Lun Chang Gung Univ Dept Comp Sci & Informat Engn Taoyuan 33302 Taiwan Providence Univ Dept Comp Sci & Commun Engn Taichung 43301 Taiwan

Array operations are useful in a lot of scientific codes. In recent years, several applications, such as the geological analysis and the medical images processing, are processed using array operations for three-dimensional (abbreviate to "3D") sparse arrays. Due to the huge computation time, it is necessary to compress 3D sparse arrays and use parallel computing technologies to speed up sparse array operations. How to compress the sparse arrays efficiently is an important task for practical applications. Hence, in this paper, two strategies, inter- and intra-task parallelization (abbreviate to "ETP" and "RTP"), are presented to compress 3D sparse arrays, respectively. Each strategy was designed and implemented on Intel Xeon and Xeon Phi, respectively. From experimental results, the ETP strategy achieves 17.5 and 18.2 speedup ratios based on Intel Xeon E5-2670 v2 and Intel Xeon Phi SE10X, respectively;4.5 and 4.5 speedup ratios for the RTP strategy based on these two environments, respectively.

关键词： Sparse array operation data compression method Parallel processing Multiprocessor Multicomputer Accelerator

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Efficient Strategies of Compressing Three-Dimensional Sparse Arrays based on Intel XEON and Intel XEON Phi Environments 15

Efficient Strategies of Compressing Three-Dimensional Sparse...

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IEEE International Conference on Computer and Information

作者： Lin, Chun-Yuan Yen, Huang Ting Hung, Che-Lun Chang Gung Univ Dept Comp Sci & Informat Engn Taoyuan 33302 Taiwan Providence Univ Dept Comp Sci & Commun Engn Taichung 433 Taiwan

ISBN: (纸本)9781509001545

Array operations are useful in a lot of important scientific codes, such as molecular dynamics, finite-element methods, atmosphere and ocean sciences, and etc. In recent years, more and more applications, such as geological analysis and medical images processing, are solved and processed by using array operations for three-dimensional (abbreviate to 3D) sparse arrays. Due to the huge computation time, it is necessary to compress the sparse arrays to compact structures in order to avoid unnecessary computations. Parallel processing is also a suitable solution to speed up the array operations based on multiprocessors, multicomputers and accelerators. How to compress the sparse arrays efficiently is the first task of designing parallel algorithms for practical applications with sparse array operations. Hence, efficient strategies of compressing 3D sparse arrays based on Intel XEON (multiprocessor) and Intel XEON Phi (accelerator) environments are proposed in this paper. For each environment, two strategies, inter-task parallelization and intra-task parallelization, are presented to compress a series of sparse arrays and single large sparse array, respectively. From experimental results, the inter-task parallelization strategy achieves 16x and 18x speedup ratios based on Intel XEON E5-2670 v2 and Intel Xeon Phi SE10X, respectively;4x and 5x speedup ratios, respectively, for the intra-task parallelization strategy.

关键词： Array operation data compression method parallel processing multiprocessor multicomputer accelerator Intel XEON Intel XEON Phi

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Geometry-Based Optimized Point Cloud compression methodology for Construction and Infrastructure Management

Geometry-Based Optimized Point Cloud Compression Methodology...

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ASCE International Workshop on Computing in Civil Engineering (IWCCE)

作者： Chen, Jiawei Zhang, Cheng Tang, Pingbo Arizona State Univ Del E Webb Sch Construct 660 South Coll Ave Tempe AZ 85281 USA

ISBN: (数字)9780784480823

ISBN: (纸本)9780784480823

Laser scanning has been widely used in as-built 3D modeling for construction and infrastructure management. When laser scanners can produce dense point clouds that capture cm-level features in minutes, efficient 3D point cloud processing, storage, and visualization remain challenging due to gigabytes of 3D imagery data. A practical solution is to compress the point cloud while keeping enough geometric information (e.g., edges, corners). Existing compression method uses uniform sampling that reduces data densities everywhere without considering that geometric complexities of different parts of a scene may deserve varying data densities. However, limited studies quantitively assess the deviations between pre-and post-compression point clouds. This research examines a laser-scanning data compression method that enables automatic compression of a point cloud with varying subsampling rates per geometric complexities of parts of data and a user-specified compression ratio (the ratio of the removed point cloud to the original point cloud, the segment with the highest value is the most compressed). Compared with qualitative methods, this method quantifies the relationship between conserved geometric details, subsampling rates, and geometric complexities. First, the developed approach takes segmented point clouds as inputs (either manual or automatic segmentation results) that contain data segments of significantly different geometric complexities depending on the shapes underlying the data segments. Next, surface smoothness and curvature are calculated to quantify the geometric complexities of point cloud segments. Then per total compression ratio, the developed approach assigns various sub-compression ratios to the segments per their geometry complexities (e.g., complicated segments are assigned higher compression ratio to keep more data and vice versa). Finally, this approach evaluates compression results by accessing deviations between the original and compressed point c

关键词： compression ratio Clouds uniform sampling geometry data DENSITY data compression method Gigabyte zero point laser scanners

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Efficient data distribution scheme for multi-dimensional sparse arrays

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JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 2007年第1期23卷 315-327页

作者： Lin, Chun-Yuan Chung, Yeh-Ching Natl Tsing Hua Univ Inst Mol & Cellular Biol Hsinchu 300 Taiwan Natl Tsing Hua Univ Dept Comp Sci Hsinchu 300 Taiwan

Array operations are useful in a large number of important scientific codes, such as molecular dynamics, finite-element methods, climate modeling, etc. It is a challenging problem to provide an efficient data distribution for irregular problems. Multi-dimensional (AM) sparse array operations can be used in atmosphere and ocean sciences, image processing, etc., and have been an extensively investigated problem. In our previous work, a data distribution scheme, Encoding-Decoding (ED), was proposed for two-dimensional (2D) sparse arrays. In this paper, ED is extended to be useful for MD sparse arrays first. Then, the performance of ED is compared with that of Send Followed Compress (SFC) and Compress Followed Send (CFS). Both theoretical analysis and experimental tests were conducted and then shown that ED is superior to SFC and CFS for all of evaluated criteria.

关键词： data compression method data distribution scheme data layout distributed memory multicomputers sparse ratio sparse array

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Model compression of SDM-based face alignment for mobile applications

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JOURNAL OF ENGINEERING-JOE 2018年第16期2018卷 1712-1718页

作者： Shen, Yehu Jiang, Quansheng Yang, Yong Wang, Bangfu Zhu, Qixin Suzhou Univ Sci & Technol Coll Mech Engn Suzhou Peoples R China Suzhou Key Lab Precis & Efficient Machining Techn Suzhou Peoples R China

Face alignment could be widely used in face recognition, expression recognition, face-based AR applications etc. Cascaded-regression-based face alignment algorithms have been popular in recent years for their low computational costs and impressive results in uncontrolled scenarios. Unfortunately, the size of the trained model is quite large for cascaded-regression-based methods which makes it unsuitable for commercial applications on mobile phones. In this study, the authors proposed a data compression method for the trained model of the supervised descent method (SDM). Firstly, the distribution of the model data was estimated using a non-parametric method. Then an adaptive quantisation algorithm was proposed to quantise the model data. Finally, their adaptive quantisation algorithm was tightly coupled with the SDM training process to fine tune the results. The quantitative experimental results proved that their proposed method could compress the data model to <20% of its original size without hurting the performances. The proposed method has been integrated into a mobile AR application, subjective evaluations proved that the proposed compression method could provide similar visual effects compared with the uncompressed counterpart.

关键词： Computer vision and image processing techniques data compression learning (artificial intelligence) model data face recognition SDM training process image coding expression recognition model compression face-based AR applications mobile phones nonparametric method regression analysis data model cascaded-regression-based methods trained model quantisation (signal) mobile applications commercial applications gradient methods low computational costs data compression method SDM-based face alignment quantitative experimental results mobile AR application adaptive quantisation algorithm cascaded-regression-based face alignment algorithms supervised descent method impressive results Other topics in statistics

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OveNet: A Hyper-Range U-Net for Singing Voice Separation

OveNet: A Hyper-Range U-Net for Singing Voice Separation

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IEEE International Symposium on Multimedia

作者： Chi-Sheng Wu Shiang Lee Von-Wun Soo Institute of Information Systems and Applications National Tsing Hua University Hsinchu Taiwan Department of Computer Science National Tsing Hua University Hsinchu Taiwan

ISBN: (数字)9781728156064

ISBN: (纸本)9781728156071

In the audio source separation topic, most researchers based on deep learning methods ignored higher-frequency signals due to lack of efficient data compression method. We propose a new model named OvertoneNet (OveNet) that adopts two novel concepts, frequency 1x1 convolution layers, and complex-spectrogram channels, to handle the 44.1k audio signals (Hi-Res audio signals) containing full overtones. The result shows that OveNet performs well in both objective and subjective evaluation on interference using limited training data from SiSEC2018.

关键词： Audio source separation Convolutional neural networks U-Net data compression method audio signals subjective evaluation Vocal music Singing Voice High definition Source separation train data Adopted harmonics

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A Novel Neural Recording System Utilising Continuous Time Energy Based compression

A Novel Neural Recording System Utilising Continuous Time En...

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IEEE International Symposium on Circuits and Systems

作者： Konstantinos Faliagkas Lieuwe B. Leene Timothy G. Constandinou Department of Electrical and Electronic Engineering Imperial College London SW7 2BT UK

ISBN: (纸本)9781479983926

This work presents a new data compression method that uses an energy operator to exploit the correlated energy in neural recording features in order to achieve adaptive sampling. This approach enhances conventional data converter topologies with the power saving of asynchronous systems while maintaining low complexity & high efficiency. The proposed scheme enables the transmission of 0.7kS/s, while preserving the features of the signal with an accuracy of 95%. It is also shown that the operation of the system is not susceptible to noise, even for signals with 1 dB SNR. The whole system consumes 3.94 μW with an estimated area of 0.093 mm~2.

关键词： data compression method Energy sources RECORDING SYSTEMS compression Hamiltonian signals data converters Resampling

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A novel method to compress high-throughput DNA sequence read archive

A novel method to compress high-throughput DNA sequence read...

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International Conference on Software Intelligence Technologies and Applications & International Conference on Frontiers of Internet of Things 2014

作者： Xiaojuan Zhan Dengju Yao College of Computer Science and Technology Heilongjiang Institute of Technology Harbin China School of Software Harbin University of Science and Technology China

The exponential growth of high-throughput DNA sequence data has brought great challenges in data processing, archive and transmission. How to improve compression techniques for large datasets of sequence read archive has become a critical problem in store and analyzes biological data. The paper compared the existing data compression methods on five high-throughput sequence datasets, and proposed a novel method to compress high-throughput sequence read archive data. The experiment results show that the proposed compression method could get good compression ration and implement higher processing speed.

关键词： DNA sequence read archive data compression high-throughput data next generation sequencing archives data compression data compression method next generation sequencing COMPRESSED DNA Sequence Exponential Growth PROCESSING SPEED dataset high speed data shopping mall

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Efficient Strategies of Compressing Three-Dimensional Sparse Arrays based on Intel XEON and Intel XEON Phi Environments

Efficient Strategies of Compressing Three-Dimensional Sparse...

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IEEE International Conference on Ubiquitous Computing and Communications

作者： Chun-Yuan Lin Huang Ting Yen Che-Lun Hung Department of Computer Science and Information Engineering Chang Gung University Taoyuan 33302 Taiwan Department of Computer Science and Communication Engineering Providence University Taichung 433 Taiwan

ISBN: (纸本)9781509001552

关键词： Array operation data compression method parallel processing multiprocessor multicomputer accelerator Intel XEON Intel XEON Phi

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