The Identification of Dog’s Identity via Rough Set Method
| Autor: | An-Bang Cheng, Kun-Li Wen |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
business.industry
Computer science 020209 energy Pattern recognition 02 engineering and technology Type (model theory) 010402 general chemistry Object (computer science) 01 natural sciences Identity (music) 0104 chemical sciences Identification (information) Calculated data Cepstrum 0202 electrical engineering electronic engineering information engineering Rough set Artificial intelligence business |
| Zdroj: | 2018 International Automatic Control Conference (CACS). |
| DOI: | 10.1109/cacs.2018.8606739 |
| Popis: | The aims of the paper is presented significant in rough set to identity the voice in difference order, Firstly, the paper uses voice recognition method to trans late the voice into digital type. Secondly, based on the calculated data that to get the Mel cepstrum parameter of the voice. Thirdly, through the significant in rough set method to identity which one is the mostly close? In the real example, the paper presents to four of dogs as the analysis object, record their barking voice, then, uses significant in rough set to find which dog is the most closest to the inspected dog. Through the actual verification, it can find that the method in our paper in the dog barking identification is quite feasible. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|