A Cihan University-Erbil Assistant Lecturer Published a Research Article with Birkhauser Boston

Adil Hussein Mohammed from the Department of Communication and Computer Engineering at Cihan University-Erbil published a research article entitled Spike Detection Based on the Adaptive Time–Frequency Analysis in the Journal of Circuits, Systems, and Signal Processing

About the author:

Name: Adil Hussein Mohammed
Qualification: MSC
Academic rank: Assistant Lecturer
Affiliation: Department of Communication and Computer Engineering, Cihan University-Erbil

Google Scholar account: https://scholar.google.com/citations?user=rw38D5MAAAAJ&hl=en


 Journal Coverage:

Title: Circuits, Systems, and Signal Processing

Science Citation Index
Science Citation Index Expanded
Clarivate Analytics (Wos: IF =1.922)
Publisher: Birkhauser Boston

Country: United States


About the Paper:

Title:Spike Detection Based on the Adaptive Time–Frequency Analysis

DOI: https://doi.org/10.1016/j.cageo.2019.104376



This paper presents a novel spike detection algorithm in nonstationary signals using a time–frequency (t–f) approach. The proposed algorithm exploits the direction of signal energy in the t–f domain to detect spikes in the presence of high-frequency nonstationary signals even at low signal-to-noise ratio. The performance of the proposed approach is evaluated using synthetic nonstationary signals, synthesized signals mimicking electroencephalogram (EEG) signals, manually selected segments of speech signals, and manually selected segments of real EEG signals. The statistical measures, such as hit rate and precision, are used to demonstrate that the proposed algorithm performs better than other widely used algorithms, such as the smoothed nonlinear energy detector.

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