Signal Processing of Microwave Imaging Brain Tumor Detection Using Superposition Windowing

• Main Authors: Chew, Kim Mey, Rubita, Sudirman, Norhudah, Seman, Yong, Ching Yee
• Format: Article
• Language: English
• Published: Trans Tech Publications Ltd 2014
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://ir.unimas.my/id/eprint/45878/2/Signal%20Processing.pdf; http://ir.unimas.my/id/eprint/45878/; https://www.scientific.net/AMM.654.321; https://doi.org/10.4028/www.scientific.net/AMM.654.321

Abstract: This paper discusses the selection of window function for signal processing in microwave imaging brain tumor detection. Most of the window functions are non-negative bell-shaped curves. This paper proposed a superposition windowing function for better time series data analyses and enhancement. The performance of the selected five window functions (Hamming, Blackman-Harris, Parzen, Chebyshev and Bartlett-Hanning) and the proposed superposition window were compared and evaluated. The results show the superposition window function is potentially reduce the unwanted noise and preserve important information of the signals.