Big data in astronomy [electronic resource] : scientific data processing for advanced radio telescopes / edited by Linghe Kong [and more]

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Bibliographic Details
Online Access: Full Text (via ScienceDirect)
Other Authors: Kong, Linghe, Huang, Tian, Zhu, Yongxin, Yu, Shenghua
Format: Electronic eBook
Language:English
Published: San Diego : Elsevier, 2020.
Subjects:

MARC

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245 0 0 |a Big data in astronomy  |h [electronic resource] :  |b scientific data processing for advanced radio telescopes /  |c edited by Linghe Kong [and more] 
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500 |a Description based upon print version of record. 
505 0 |a Intro -- Big Data in Astronomy: Scientific Data Processing for Advanced Radio Telescopes -- Copyright -- Contents -- Contributors -- Preface -- Acknowledgments -- Part A: Fundamentals -- Chapter 1: Introduction to radio astronomy -- 1. The history of astronomy -- 1.1. Ancient astronomy -- 1.2. Astronomy from the mid-16th century to the mid-19th century -- 1.3. Astronomy since the mid-19th century -- 2. What is radio astronomy -- 2.1. How does radio astronomy occur -- 2.2. The radio stars, quasars, and black holes -- 2.2.1. The strongest radio source, Cygnus A, in the sky. 
505 8 |a 2.2.2. The discovery of cliff allergens and radio galaxies -- 2.2.3. Nonthermal radiation -- 2.2.4. Synchronous radiation -- 2.2.5. Synchrotron radiation pattern -- 2.2.6. Connect nonthermal radiation and cosmic rays -- 2.2.7. Astrophysics of cosmic rays -- 2.2.8. Discovery of quasars -- 2.3. The radio astronomy instrument: Radio telescope -- 2.4. Some achievements of radio astronomy -- 2.5. Astronomical research nowadays -- 3. Advanced radio telescope -- 3.1. The square kilometer array (SKA) -- 3.2. Fast -- 4. The challenge of radio astronomy -- 4.1. System noise. 
505 8 |a 4.2. Antennas and collecting area -- 4.3. Data transmission -- 5. The development tendency of radio astronomy -- 5.1. Mid-frequency aperture arrays -- 5.2. Entering a near future -- References -- Chapter 2: Fundamentals of big data in radio astronomy -- 1. Big data and astronomy -- 1.1. Background of big data -- 1.2. Definitions and features of big data -- 1.3. Development of big data -- 1.4. Big data in astronomy -- 1.5. Statistical challenges in astronomy -- 2. Increasing data volumes of telescopes -- 2.1. Sloan digital sky survey -- 2.2. Visible and infrared survey telescope for astronomy. 
505 8 |a 2.3. Large synoptic survey telescope -- 2.4. Thirty meter telescope -- 3. Existing methods for the value chain of big data -- 3.1. Data generation -- 3.2. Data acquisition -- 3.3. Data storage -- 3.4. Data analysis -- 3.4.1. Traditional data analysis methods -- 3.4.2. Big data analytic methods -- 3.4.3. Architecture for big data analysis -- 4. Current statistical methods for astronomical data analysis -- 4.1. Nonparametric statistics -- 4.2. Data smoothing -- 4.3. Multivariate clustering and classification -- 4.4. Nondetections and truncation -- 4.5. Spatial point processes. 
505 8 |a 5. Platforms for big data processing -- 5.1. Horizontal scaling platforms -- 5.2. Vertical scaling platforms -- 5.2.1. High performance computing (HPC) clusters -- 5.2.2. Multicore CPU -- 5.2.3. Graphics processing unit (GPU) -- 5.2.4. Field programmable gate arrays (FPGA) -- References -- Part B: Big data processing -- Chapter 3: Preprocessing pipeline on FPGA -- 1. FPGA interface for ADC -- 1.1. ADC interleaving -- 1.2. Bit alignment -- 1.3. Stream deserialization -- 2. FIR filtering -- 2.1. Leakage -- 2.2. Scalloping loss -- 2.3. Polyphase filter -- 3. Time-frequency domain transposing. 
500 |a 3.1. Real-valued FFT. 
650 0 |a Radio astronomy  |x Data processing. 
650 0 |a Big data.  |0 http://id.loc.gov/authorities/subjects/sh2012003227. 
700 1 |a Kong, Linghe.  |0 http://id.loc.gov/authorities/names/nr96014559  |1 http://isni.org/isni/000000006429159X. 
700 1 |a Huang, Tian.  |0 http://id.loc.gov/authorities/names/n88073449. 
700 1 |a Zhu, Yongxin.  |0 http://id.loc.gov/authorities/names/n85176079  |1 http://isni.org/isni/0000000063598928. 
700 1 |a Yu, Shenghua. 
776 0 8 |i Print version:  |a Kong, Linghe  |t Big Data in Astronomy : Scientific Data Processing for Advanced Radio Telescopes  |d San Diego : Elsevier,c2020. 
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