Instantaneous Spectrum Analysis Research Articles

Prefrontal Brain Electrical Activity and Cognitive Load Analysis Using a Non-linear and Non-Stationary Approach

This study presents an instantaneous spectrum analysis for electroencephalograph data processing that would facilitate the practice of learning and instruction through real-time measurements of the learner's cognitive load. The instantaneous spectrum analysis is derived from the ensemble empirical mode decomposition which decomposes signals into a gathering of intrinsic mode functions without mode mixing. The multi-marginal Hilbert-Huang spectrum is introduced to estimate frequency contents. As a result, the amplitude of brain rhythms related to the cognitive load can be determined accurately. A model study was performed at first to test the efficacy of the proposed algorithm by comparing with the Fourier based technique, then a prefrontal experiment was conducted to show the advantages of the proposed method. With the higher resolution and more realistic of the proposed method relative to conventional spectrum analysis, more significant features of the signal can be extracted. We believe that the proposed method has the potential to be a substantial technique in electroencephalograph data analysis.

Whispered Speech Detection Using Fusion of Group-Delay-Based Subband Modulation Spectrum and Correntropy Features

In this letter, we propose a novel fusion feature for detection of whispered speech in noisy environment using a group-delay-based instantaneous spectrum analysis. The fusion feature involves two individual components, namely, subband modulation spectrum (SMS)-based features and subband correntropy (SCE) features, both extracted from the instantaneous spectrum. The instantaneous spectrum estimation involves zero-time windowing for improved temporal resolution and group-delay computation for improved spectral resolution, as compared to the traditional discrete-Fourier-transform-based spectrum estimation. The SMS features capture the spectral representation of the subband energy time trajectories, while the SCE features model the fluctuations in the subband energy time trajectories. The SMS captures both the short-term as well as long-term spectral characteristics of whispered speech and is known to provide good separation between speech and noise components. The correntropy features help capture the dynamics of the vocal tract system to discriminate noisy whisper from noise. Whisper speech detection experiments using support vector machine models and the proposed features indicate promising performance under low signal-to-noise conditions.

Identification of the Spectrum Signature of Air-Bearing Slider Dynamics

Characterization of the motion of air-bearing slider with sub-10-nm clearance is becoming a critical aspect of developing advanced head–disk interfaces (HDI) in hard disk drives to achieve higher areal data densities. In this article, the response of sub-10-nm clearance air-bearing slider induced by a bump contact is recorded using laser Doppler vibrometer (LDV). To identify system dynamics in terms of spectral decomposition, the slider response is studied using FFT, power spectrum density, spectrogram, and Hilbert instantaneous spectrum analysis. The results demonstrate that the response of air-bearing slider in instantaneous contact exhibits nonstationary and nonlinear properties which can be accurately identified using Hilbert instantaneous spectrum. The interpretation and spectrum identification based on Fourier analysis and its extension in time–frequency domain could lead to inaccurate results due to their limitation in resolution and linearity assumption.

Intensity analysis methods for transient signals

Conventionally, the Fourier transform is applied for sound intensity analysis of stationary signals, but this method can be applied for analyzing non-stationary transient signals. Instead of the Fourier transform analysis, instantaneous spectrum analysis methods such as the Wigner–Ville distribution and the wavelet transform are proposed. By using the mathematical example as a transient signal, advantages and disadvantages of these methods including the short-time Fourier transform are compared. From calculation results, it is considered that the STFT method is the most suitable for the accurate measurement of sound intensity levels, but the WT method is also recommended from its higher resolution of transient signals.

Instantaneous spectrum analysis and its application in estimation of earthquake tendency

In this paper, first discussing briefly the instantaneous spectrum theory. Then, the instantnaeous spectra and Fourier spectra of three seismic sequences are calculated, and comparing them to explain the superior characteristics of instantaneous spectrum. Finally, the earthquake tendency of North China is estimated by using the instantaneous spectrum theory. The results show that not only the occurrence time of the coming large earthquake, but also its magnitude instantaneous can be estimated by using instantaneous spectrum of the seismic sequence.