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.

中文翻译：

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基于自适应时频分析的尖峰检测

本文提出了一种使用时频 (t – f) 方法在非平稳信号中检测尖峰的新算法。所提出的算法利用 t-f 域中的信号能量方向来检测高频非平稳信号存在时的尖峰，即使在低信噪比下也是如此。使用合成非平稳信号、模拟脑电图 (EEG) 信号的合成信号、手动选择的语音信号段和手动选择的真实 EEG 信号段来评估所提出方法的性能。统计测量，如命中率和精度，用于证明所提出的算法比其他广泛使用的算法（如平滑非线性能量检测器）的性能更好。