| DC Field | Value | Language |
|---|
| dc.contributor.author | Zhao Di | - |
| dc.date.accessioned | 2022-05-14T09:41:36Z | - |
| dc.date.available | 2022-05-14T09:41:36Z | - |
| dc.date.issued | 2022 | - |
| dc.identifier.citation | Zhao Di. Sensor data frequency feature extraction / Zhao Di // Технологии передачи и обработки информации : материалы международного научно-технического семинара, Минск, март-апрель 2022 г. / Белорусский государственный университет информатики и радиоэлектроники. – Минск, 2022. – С. 66–68. | ru_RU |
| dc.identifier.uri | https://libeldoc.bsuir.by/handle/123456789/46943 | - |
| dc.description.abstract | Frequency domain features are important for human activity recognition. However, the raw signal needs to be converted to frequency domain features using a fast Fourier transform. In the frequency domain, the time series data of each component is converted by using the Fast Fourier Transform (FFT) algorithm. | ru_RU |
| dc.language.iso | en | ru_RU |
| dc.publisher | БГУИР | ru_RU |
| dc.subject | материалы конференций | ru_RU |
| dc.subject | Fast Fourier algorithm | ru_RU |
| dc.subject | Feature extraction | ru_RU |
| dc.title | Sensor data frequency feature extraction | ru_RU |
| dc.type | Статья | ru_RU |
| Appears in Collections: | Технологии передачи и обработки информации : материалы международного научно-технического семинара (2022)
|
