Select Language

公开数据集

低分辨率光谱仪数据集,IRAS-LRS数据库的531个高质量光谱

低分辨率光谱仪数据集,IRAS-LRS数据库的531个高质量光谱

Scene:

Physical

Data Type:

Classification
所需积分:10 去赚积分?
  • 240浏览
  • 3下载
  • 1点赞
  • 收藏
  • 分享

Data Preview ? 477K

    Data Structure ?

    *数据结构实际以真实数据为准

    Data Set Information:

    红外天文卫星(IRAS)是第一次尝试在红外波段绘制全天图。地面观测站无法做到这一点,因为大部分红外光谱被大气吸收。主要的观测项目是通过在4个频率进行扫描进行的全高分辨率天空测绘。低分辨率观测(IRAS-LRS)计划在两个连续谱带上观测到高强度源。该数据库来自于在赤经12小时和24小时之间进行的高质量LRS观测的子集。


    该数据库包含来自IRAS-LRS数据库的531个高质量光谱。原始数据包含两个重叠波段各100个光谱测量值。其中,44个蓝带和49个红带通道包含可用的通量测量。这里只包括这些。原始光谱强度值压缩为4位数字,每个光谱包括5个重缩放参数。我们已使用LRS指定的算法将其重新缩放为光谱强度单位(Janskys)。通过将每个光谱标准化为5000的平均值,消除了总强度差异。


    该数据库最初用于开发和测试我们的自动分类系统,用于贝叶斯分类。我们没有保留这一发展的任何结果,我们集中精力研究同一数据的5425个元素版本。我们的分类基于所有93个光谱强度的同时建模。通过更大的数据库,我们能够找到与特定恒星类型相关的已知光谱类型完全对应的类。我们还发现了与艾姆斯天文学家所研究的某些恒星过程的预期光谱相匹配的类。这些类别大大扩大了这些研究人员正在研究的恒星的范围。


    Original data:

    The original fortran data file is given in spectra-2.data.  The file spectra-2.head contains information about the .data file contents and how to rescale the compressed spectral intensities.


    Attribute Information:

    1. LRS-name: (Suspected format: 5 digits, "+" or "-", 4 digits)
       2. LRS-class: integer - The LRS-class values range from 0 - 99 with the 10's digit giving the basic class and the 1's digit giving the subclass. These classes are based on features (peaks, valleys, and trends) of the spectral curves.  
       3. ID-type: integer
       4. Right-Ascension: float - Astronomical longitude. 1h = 15deg
       5. Declination: float - Astronomical lattitude. -90 <= Dec <= 90
       6. Scale Factor: float - Proportional to source strength
       7. Blue base 1: integer - linear rescaling coefficient
       8. Blue base 2: integer - linear rescaling coefficient
       9. Red base 1: integer - linear rescaling coefficient
      10. Red base 2: integer - linear rescaling coefficient
      11-54: fluxes from the following 44 blue-band channel wavelengths: (all given as floating point numerals)
        - 11. 7.8636
        - 12. 8.0485
        - 13. 8.2286
        - 14. 8.4043
        - 15. 8.5758
        - 16. 8.7436
        - 17. 8.9078
        - 18. 9.0686
        - 19. 9.2262
        - 20. 9.3809
        - 21. 9.5328
        - 22. 9.6820
        - 23. 9.8286
        - 24. 9.9728
        - 25. 10.1148
        - 26. 10.2545
        - 27. 10.3922
        - 28. 10.5279
        - 29. 10.6616
        - 30. 10.7935
        - 31. 10.9237
        - 32. 11.0521
        - 33. 11.1790
        - 34. 11.3042
        - 35. 11.4280
        - 36. 11.5503
        - 37. 11.6711
        - 38. 11.7907
        - 39. 11.9089
        - 40. 12.0258
        - 41. 12.1415
        - 42. 12.2560
        - 43. 12.3693
        - 44. 12.4816
        - 45. 12.5927
        - 46. 12.7028
        - 47. 12.8118
        - 48. 12.9199
        - 49. 13.0269
        - 50. 13.1330
        - 51. 13.2382
        - 52. 13.3425
        - 53. 13.4459
        - 54. 13.5485
       55-103: fluxes from the following 49 red-band channel wavelengths: (all given as floating point numerals)
        - 55. 10.9929
        - 56. 11.3704
        - 57. 11.7357
        - 58. 12.0899
        - 59. 12.4339
        - 60. 12.7687
        - 61. 13.0948
        - 62. 13.4131
        - 63. 13.7239
        - 64. 14.0278
        - 65. 14.3252
        - 66. 14.6166
        - 67. 14.9022
        - 68. 15.1825
        - 69. 15.4576
        - 70. 15.7280
        - 71. 15.9937
        - 72. 16.2551
        - 73. 16.5123
        - 74. 16.7656
        - 75. 17.0151
        - 76. 17.2610
        - 77. 17.5034
        - 78. 17.7425
        - 79. 17.9784
        - 80. 18.2113
        - 81. 18.4412
        - 82. 18.6682
        - 83. 18.8925
        - 84. 19.1142
        - 85. 19.3334
        - 86. 19.5500
        - 87. 19.7643
        - 88. 19.9763
        - 89. 20.1861
        - 90. 20.3937
        - 91. 20.5992
        - 92. 20.8026
        - 93. 21.0041
        - 94. 21.2037
        - 95. 21.4014
        - 96. 21.5973
        - 97. 21.7914
        - 98. 21.9838
        - 99. 22.1745
        - 100. 22.3636
        - 101. 22.5511
        - 102. 22.7371
        - 103. 22.9216


    Relevant Papers:

    A NASA-Ames research group concerned with unsupervised learning tasks may have used this database during their empirical studies of their algorithm/system (AUTOCLASS II).  See the 1988 Machine Learning Conference Proceedings, 54-64, for a description of their algorithm.


    Citation Request:

    Please refer to the Machine Learning Repository's citation policy


    Originator:

    Infra-Red Astronomy Satellite Project Database

    Donor:

    John Stutz <STUTZ '@' pluto.arc.nasa.gov>
    It's possible that one of John's colleagues actually provided this to UCI, perhaps Mike Marshall (MARSHALL%PLU '@' io.arc.nasa.gov)




    0相关评论
    ×

    帕依提提提温馨提示

    该数据集正在整理中,为您准备了其他渠道,请您使用

    注:部分数据正在处理中,未能直接提供下载,还请大家理解和支持。