| The least-square method in complex number domain |
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| 作者姓名： | GU Xiangqian KANG Hongwen CAO Hongxing |
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| 作者单位： | State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China |
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| 基金项目： | Supported by National Natural Science Foundation of China (Grant No. 40175027) |
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| 摘 要： | The classical least-square method was extended from the real number into the complex number domain, which is called the complex least-square method. The mathematical derivation and its applications show that the complex least-square method is different from one that the real number and the imaginary number are separately calculated with the classical least-square, by which the actual least-square estimation cannot be obtained in practice. Applications of this new method to an arbitrarily given series and to the precipitation in rainy season at 160 meteorological stations in China mainland show advantages of this method over other conventional statistical models.
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| 关 键 词： | complex least square Fourier transformation forecast in rainy season. |
The least-square method in complex number domain |
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| GU Xiangqian,KANG Hongwen,CAO Hongxing.The least-square method in complex number domain[J].Progress in Natural Science,2006,16(3):307-312. |
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| Authors: | GU Xiangqian KANG Hongwen CAO Hongxing |
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| Institution: | State Key Laboratory of Severe Weather,Chinese Academy of Meteorological Sciences,Beijing 100081,China |
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| Abstract: | The classical least-square method was extended from the real number into the complex number domain, which is called the complex least-square method. The mathematical derivation and its applications show that the complex least-square method is different from one that the real number and the imaginary number are separately calculated with the classical least-square, by which the actual least-square estimation cannot be obtained in practice. Applications of this new method to an arbitrarily given series and to the precipitation in rainy season at 160 meteorological stations in China mainland show advantages of this method over other conventional statistical models. |
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| Keywords: | complex least square Fourier transformation forecast in rainy season |
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