Poignant ground target recognition with Smooth Pseudo Wigner-Ville Distribution by Analysis of Time-Frequency Techniques
- Title
- Poignant ground target recognition with Smooth Pseudo Wigner-Ville Distribution by Analysis of Time-Frequency Techniques
- Abstract
- Humans have had the ability to recognise items for hundreds of years, possibly even since they first appeared on Earth. All of the senses sight, smell, hearing, taste, and touch play a role in helping humans determine what is in their immediate vicinity. In order to integrate and make sense of the information picked up by the senses, the brain receives signals from those organs. Repetition of an experience has been shown to improve cognition. The learned knowledge is put to use in a wide variety of ways, from the mundane to the crucial, such as in the areas of security, surveillance, traffic monitoring, and so on. Human senses are limited to a relatively small range, and it could be dangerous or even fatal to work in some settings. This study provides a comprehensive evaluation of the many time- frequency methods now in use for finding targets. Furthermore, a unique method for detecting targets utilising an improved time-frequency representation of the seismic data is outlined in this research paper. When compared to solely time-domain or frequency-domain methods, time-frequency domain analyses do better. Because traditional time domain and frequency domain analysis methods only reveal one aspect of a signal at a time, time-frequency methods reveal both aspects at once.
- Scientific Type
- غير معروف
- Journal volume
- 23241636
- Collaboration type
- مشترك
- Publish Date
- June 7, 2023
- Participated Universities (Publication)
-
Alnoor University
- Scopus status
- In Scopus
- Scopus index year
- 2 023
- Scopus quarter
- 5
- Clarivate status
- Not In Clarivate
- Pub. Med. status
- Not In PubMed
- Author (Publication)
- ملاك جعفر علي غائب
- Journal (Publication)
- 2023 International Conference on Computational Intelligence
- Publisher (Publication)
-
IEEE Xplore
- ISSN
- 979-835033802-7
- Country (Publication)
-
India
- Country type
- عالمية
- College (Publication)
-
College of Health and Medical Technologies
- Departement (Publication)
-
Department of Radiology
- Media
-
Academic Paper
