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Classification of Hand Motion Using Surface EMG Signals
Published in Yunhui Liu, Dong Sun, Biologically Inspired, 2017
Xueyan Tang, Yunhui Liu, Congyi Lu, Weilun Poon
A high spectral flatness indicates that the spectrum has a similar amount of power in all spectral bands. A low spectral flatness indicates that the spectral power is concentrated within a relatively small number of bands.
Damage detection of a cable-stayed bridge based on combining effective intrinsic mode functions of empirical mode decomposition using the feature selection technique
Published in Inverse Problems in Science and Engineering, 2021
Hossein Babajanian Bisheh, Gholamreza Ghodrati Amiri, Masoud Nekooei, Ehsan Darvishan
The following descriptors represent the shape of the STFT using Equations (19)–(24), as listed in Table 3. The spectral roll off (S5) measures the bandwidth of the analysed block n of the samples.The spectral flux (S6) represents the amount of variation in the spectral shape. It is defined as the mean difference between successive STFT frames.The spectral decrease (S7) computes the steepness of the decrease of the spectral envelope over frequency.The spectral slope (S8) measures the slope of the spectral shape using a linear regression over the spectral amplitude values.The spectral crest factor (S9) is the ratio of the maximum value of the magnitude spectrum to the sum of the magnitude spectrum.The spectral flatness (S10) is obtained by comparing the geometric and arithmetic means of the spectrum.
Damage detection of a cable-stayed bridge using feature extraction and selection methods
Published in Structure and Infrastructure Engineering, 2019
Hossein Babajanian Bisheh, Gholamreza Ghodrati Amiri, Masoud Nekooei, Ehsan Darvishan
The following features describe the shape of the (magnitude spectrum of the) STFT using Equations (18)–(23), as listed in Table 3: The spectral roll off (S5) is a measure of the bandwidth of the analysed block n of the samples.The spectral flux (S6) measures the amount of change of the spectral shape. It is defined as the average difference between consecutive STFT frames.The spectral decrease (S7) estimates the steepness of the decrease of the spectral envelope over frequency.The spectral slope (S8) is similar to the spectral decrease, a measure of the slope of the spectral shape.Spectral Crest Factor (S9) compares peaks of the magnitude spectrum with the sum of this magnitude spectrum).Spectral Flatness (S10) is the ratio of geometric mean to the arithmetic mean of the magnitude spectrum.
Gender and region detection from human voice using the three-layer feature extraction method with 1D CNN
Published in Journal of Information and Telecommunication, 2022
Mohammad Amaz Uddin, Refat Khan Pathan, Md Sayem Hossain, Munmun Biswas
Spectral flatness: It is a feature of acoustic signals which is useful in digital signal processing (Madhu, 2009). Generally, the ratio of the geometric mean to the arithmetic mean of a power spectrum is known as spectral flatness. It is mainly used to quantify the noise-like or tone-like nature of a sound signal. Using spectral flatness, we can find out the flat or non-flat position of a signal. If the ratio of arithmetic mean and geometric mean is 1 and a power spectrum is perfectly flat, then it means the arithmetic mean and geometric mean are equal. Although, the ratio can’t be more than 1, because the geometric mean is always greater or equal than the arithmetic mean.