C-Worm Traffic Detection using Power Spectral Density and Spectral Flatness Measure

Efficient voice activity detection algorithm using long-term spectral flatness measure

This paper proposes a novel and robust voice activity detection (VAD) algorithm utilizing long-term spectral flatness measure (LSFM) which is capable of working at 10 dB and lower signal-to-noise ratios(SNRs). This new LSFM-based VAD improves speech detection robustness in various noisy environments by employing a low-variance spectrum estimate and an adaptive threshold. The discriminative powe...

Erratum to: Efficient voice activity detection algorithm using long-term spectral flatness measure

Maximum flatness spectral modeling

The maximum entropy method obtains the flattest spectrum consistent with the given autocorrelation values, according to a specific flatness measure. In this correspondence, the suitability of the maximum flatness criterion for spectral estimation is discussed, concluding that it offers useful insight into the spectral models arising from the optimization approach.

A Segmental Spectral Flatness Measure for Harmonic-Percussive Discrimination

In a variety of applications of audio signal processing, for example blind source separation (BSS), harmonic signals need to be treated differently from percussive signals. Thus, recognizing if a signal is harmonic or percussive is a very helpful and frequently used preprocessing step. Different measures have been proposed to capture either the harmonicity or the percussivity of a signal, using...

Nonparametric Spectral-Spatial Anomaly Detection

Due to abundant spectral information contained in the hyperspectral images, they are suitable data for anomalous targets detection. The use of spatial features in addition to spectral ones can improve the anomaly detection performance. An anomaly detector, called nonparametric spectral-spatial detector (NSSD), is proposed in this work which utilizes the benefits of spatial features and local st...