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1)  Xingsheng
形声
1.
Based on the achievements made by predecessors,the paper gives the new explanation to the development of Chinese character-formation in "Liushu",especially to Jiajie(phonetic loan character),Zhuanzhu(mutually explanatory or synonymous characters) and Xingsheng(shape and sound)in order to evaluate the traditional assessment of "Liushu".
本文在吸取众多学者有益成果的基础上,对传统"六书"作为汉字构形的演化,尤其对其中的"假借、转注、形声"进行了分析和评价。
2.
Some Huiyi and Xingsheng characters have m ore than two Yifas.
汉字中部分会意字和形声字含有2个或2个以上的意符,根据意符的特点与数量,对《说文解字》中的多意符会意字和形声字进行分类、统计,并指出意符在汉字结构体系中的重要性及对汉字简化和规范化的潜在价值和意义。
2)  Phonopictorial
声形
3)  acoustic waveform
声波波形
4)  Circumferential acoustical device
环形声波
5)  pictophonetic characters
形声字
1.
Analysis of Chinese as a Foreign Language Teaching of Pictophonetic Characters
浅析对外汉语教学中的形声字教学
2.
Beginning from the lesser seal characters, pictophonetic characters became the main stream of the development of the Chinese characters.
从小篆开始形声字成为汉字发展的主流,对其研究不仅能深化对形声字本身的认识,而且对认清整个汉字系统的发展也有重要意义。
3.
That "Phoneme" conveys some meaning of the word itselfin pictophonetic characters is a fundamental principle in writing ghe Chinese pictophonetic characters.
形声字“声符”表意是形声型汉字写词中的一条基本规律。
6)  Fractal noise
分形噪声
1.
Detection of BPSK signals from fractal noise based on wavelet spectral correlation
分形噪声中BPSK信号检测的小波谱相关方法研究
2.
The theoretic analysis show when Snr>5dB:(1)the affection of fractal noise is so light that the classification feature retain a distinct boundary.
提取了盒维数、信息维数和高阶分形特征-缝隙尺度变化率构成分类特征向量空间,这些特征包含了信号幅度、频率和相位的变化规律,集中了各种调制方式之间的差异信息,通过理论分析和仿真表明,当 SNR>5dB 时,(1)分形特征对分形随机噪声不敏感,能充分保证分类特征在决策空间存在一个较清晰的边界;(2)在相同的 SNR 环境下,分形特征在分形噪声环境下比在高斯白噪声环境下有更好的稳定性,对5种调制样式的识别率均大于92。
3.
In this paper, using R/S analysis method, through fractal noise that describes fractional Brownian motion and the relationship between fractal noise and H value of Hurst exponent, the noise color of price behavior of Shanghai stock market is tested empirically.
运用R/S分析方法,通过分析分形布朗运动的分形噪声及其与Hurst指数H值之间的对应关系,实证检验了上海股市价格行为中存在的噪声色彩。
补充资料:形声
      见六书。
  

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