A novel STFT implementation for the analysis of non-stationary jammer interference
Date
2004Journal Title
Proceedings of the Fourth IASTED International Multi-Conference on Wireless and Optical Communications
Pages
279 - 284
Language
English
Type
Conference PaperItem Usage Stats
20
views
views
7
downloads
downloads
Metadata
Show full item recordAbstract
A novel adaptive short-time Fourier transform (STFT) implementation for the analysis of non-stationary multi-component jammer signals is introduced. The proposed time-frequency distribution is the fusion of optimum STFTs of individual signal components that are based on the recently introduced generalized time-bandwidth product (GTBP) definition. The GTBP optimal STFTs of the components are combined through thresholding and obtaining the individual component support images, which are related with the corresponding GTBP optimal STFTs.
Keywords
Generalized time-bandwidth productLinear time-frequency distributions
Multi-component chirp jammers
Non-stationary signal analysis
Short-time Fourier transform
Bandwidth
Computational methods
Fourier transforms
Frequency domain analysis
Frequency modulation
Optimization
Time domain analysis
Transmitters
Generalized time-bandwidth product (GTBP)
Linear time-frequency distributions
Multi-component chirp jammers
Non-stationary signal analysis
Short-time Fourier transform (STFT)
Jamming
Permalink (Please cite this version)
http://hdl.handle.net/11693/27407Collections
Related items
Showing items related by title, author, creator and subject.
-
Statistical analysis methods for the fMRI data
(2011)Functional magnetic resonance imaging (fMRI) is a safe and non-invasive way to assess brain functions by using signal changes associated with brain activity. The technique has become a ubiquitous tool in basic, clinical ... -
Accumulation trends of metals and a metalloid in the freshwater crayfish Astacus leptodactylus from Lake Yeniçağa (Turkey)
(2013)This study aims to determine the extent of metal pollution in Lake Yeniçaǧa (Bolu, Turkey) by investigating the accumulation trends of five metals (Al, Cu, Fe, Ni and Zn) and a metalloid (As) in gills, exoskeleton, ... -
Unsupervised tissue image segmentation through object-oriented texture
(2010)This paper presents a new algorithm for the unsupervised segmentation of tissue images. It relies on using the spatial information of cytological tissue components. As opposed to the previous study, it does not only use ...
