頁籤選單縮合
題名 | The Identification of Dog's Identity via GM(0,N) and Regression Analysis= |
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作者 | Chen, Mao-lin; Fang, Chien-tien; Lin, Kuo-chuan; |
期刊 | Journal of Grey System |
出版日期 | 20151200 |
卷期 | 18:4 2015.12[民104.12] |
頁次 | 頁225-231 |
分類號 | 400.24 |
語文 | eng |
關鍵詞 | GM(0,N); Dog barking; Regression analysis; Gold Wave; Weighting; |
英文摘要 | The main purpose of the paper is applied the GM (0, N) model in grey system theory to identity the same kinds of dog barking voice in difference order, and also use regression analysis to verify the final result . Firstly, the paper uses Speech Filing System software to transfer the dog voice into the eigen-value state. Secondly, use Gold Wave to filter the voice signal, and translate the value of eigen-value state into digital type, to build up the inspected dog's barking voice. Finally, through GM (0, N) model to identity the dog barking voice. And use the maximum weighting to identity which one is the most closely to the inspected dog, also use regression analysis to double check the result. Through the real example by using four differences shibu inu, show the method that in our paper is quite successfully. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。