(PSK), Analysis method is based on the spectrogram time frequency analysis and a rule based approach is used as a classifier.From the time-frequency representation,the instantaneous frequency is estimated which is then used to estimate the modulation type its parameters.This information is further ...
potential (MRCP) analysis, power spectrum analysis, time-frequency (spectrogram) analysis of EEG, EEG source localization and nonlinear analysis (fractal dimension and largest Lyapunov exponent), and fMRI analysis, was applied to the data... Y Bing - 《Brain》 被引量: 1发表: 2006年 On the...
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To exploit the short-term stationarity of audio signals, it is very often applied on time-frequency representations, especially the short-time Fourier transform (STFT). However, classical Wiener filtering does not take into account the intrinsically redundant structure of STFT spectrograms, and its ...
aThe corresponding numerically calculated pulse temporal intensity profile and numerical and experimental second-harmonic generation frequency-resolved optical gating (SHG FROG) spectrograms are also shown in Fig . 2. 数字对应计算了脉冲世俗强度外形,并且数字和实验性二泛音世代频率解决的光学给装门的 (SHG...
Analytical spectrograms aimed at achieving maximum frequency resolution are presented using linear scaling, where every row of pixels is evenly spaced in the frequency domain. However, biological sensory systems tend to be logarithmic, and the human ear can differentiate frequency shifts better at lower...
autofft - A time-frequency analyser for Matlab The Signal Processing Toolbox™ provides several functions to power spectrum estimation, includingpspectrum,pwelchandstft. Although these functions are of high quality and well-documented, they might be cumbersome in some engineering applications. These ...
Analytical spectrograms aimed at achieving maximum frequency resolution are presented using linear scaling, where every row of pixels is evenly spaced in the frequency domain. However, biological sensory systems tend to be logarithmic, and the human ear can differentiate frequency shifts better at lower...
(KNN) classifier. The results obtained confirm that the KNN classifier is helpful in the rapid detection of schizophrenia. This work is one of the first studies to extract local configuration pattern features from spectrogram images, yielding a high accuracy of 97.20%, with reduced computational ...