scholarly journals A new spectrum feature discovered for a category of signals produced by massive and random micro-sources

2018 ◽  
Vol 210 ◽  
pp. 05010
Author(s):  
Xiaodong Zhuang ◽  
Nikos Mastorakis
Keyword(s):  
Statistical Study ◽  
Amplitude Spectrum ◽  
Time Spectrum ◽  
Frequency Component ◽  
Main Category ◽  
Frequency Components ◽  
Spectrum Feature ◽  
Short Time ◽  
The Relationship ◽  
System Characteristics

A statistical study is implemented on the short-time spectrum of one main category of random signals. For the signals with massive and random micro-sources, a new statistic feature of the short-time amplitude spectrum is discovered, which reveals the relationship between the amplitude’s average and its standard for each frequency component. Moreover, the association between the amplitude distributions for different frequency components is also studied. A model representing such association is presented, which accords well with the statistic feature discovered. The analysis result has potential application in signal classification, and also in the study of system characteristics underlying the observed signal.

scholarly journals Signal Processing: New Stochastic Feature of Unvoiced Pronunciation for Whisper Speech Modeling and Synthesis

2021 ◽  
Vol 14 ◽  
pp. 1162-1175
Author(s):  
X. D. Zhuang ◽  
H. Zhu ◽  
N. E. Mastorakis
Keyword(s):  
Amplitude Spectrum ◽  
Research Work ◽  
Synthesis Method ◽  
Time Spectrum ◽  
Frequency Component ◽  
Speech Communication ◽  
Human Machine Interaction ◽  
New Feature ◽  
Deviation Coefficient ◽  
Short Time

Whisper is an indispensable way in speech communication, especially for private conversation or human-machine interaction in public places such as library and hospital. Whisper is unvoiced pronunciation, and voiceless sound is usually considered as noise-like signals. However, unvoiced sound has unique acoustic features and can carry enough information for effective communication. Although it is a significant form of communication, currently there is much less research work on whisper signal than common speech and voiced pronunciation. Our work extends the research of unvoiced pronunciation signal by introducing a novel signal feature, which is further applied in unvoiced signal modeling and whisper sound synthesis. The statistics of amplitude for each frequency component is studied individually, based on which a new feature of “consistent standard deviation coefficient” is revealed for the amplitude spectrum of unvoiced pronunciation. A synthesis method for unvoiced pronunciation is proposed based on the new feature, which is implemented by STFT with artificially generated short-time spectrum with random amplitude and phase. The synthesis results have identical quality of auditory perception as the original pronunciation, and have similar autocorrelation as that of the original signal, which proves the effectiveness of the proposed stochastic model of short-time spectrum for unvoiced pronunciation

scholarly journals Barycenter Theorem in Phase Characteristics of Symmetric and Asymmetric Windows

Symmetry ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 329
Author(s):  
Jiufei Luo ◽  
Haitao Xu ◽  
Kai Zheng ◽  
Xinyi Li ◽  
Song Feng
Keyword(s):  
Frequency Estimation ◽  
Random Noise ◽  
Estimation Algorithm ◽  
Frequency Component ◽  
Phase Response ◽  
Numeric Simulation ◽  
Simulation Results ◽  
The Time Domain ◽  
Short Time ◽  
The Relationship

Asymmetric windows are of increasing interest to researchers because of the nonlinear and adjustable phase response, as well as alterable time delay. Short-time phase distortion can provide an essential improvement in speech coding, and also has better performance in speech recognition. The merits of asymmetric windows in the aspect of spectral behaviors have an important function in frequency component detection and parameter estimation. In this paper, the phase response of windows were further studied, and the phase characteristics of symmetric and asymmetric windows are described. The relationship between the barycenter of windows in the time domain, and the phase characteristic at the center of the main lobe in the frequency domain, was established. In light of the relationship, an improved version of the asymmetric window- based frequency estimation algorithm was proposed. The improved algorithm has advantages of straightforward implementation and computational efficiency. The numeric simulation results also indicate that the improved approach is more robust than the traditional method against additive random noise.

Feature Analysis of Mechanical Fault Signals Based on the Wavelet Transform Technique

2010 ◽  
Vol 139-141 ◽  
pp. 2502-2505
Author(s):  
Bing Cheng Wang ◽  
Zhao Hui Ren
Keyword(s):  
High Frequency ◽  
Amplitude Spectrum ◽  
Low Frequency ◽  
Feature Analysis ◽  
Oil Whip ◽  
Frequency Components ◽  
Quantitative Manner ◽  
Beat Phenomenon ◽  
The Impact ◽  
The Relationship

Simulated four different fault signals in the lab, the authors then used wavelet scalogram and amplitude spectrum to make analysis on the above four fault signals and abstract each spectrum characteristics. Wavelet scalogram was able to extract the characteristic’s frequency, show the impact components caused by rub-impact, show the beat phenomenon caused by oil whip and show the irreducible high frequency components as well as the complex low-frequency components. Amplitude spectrum was able to show the energy size distribution at various frequency bands and able to analyze and calculate the relationship between various frequency components. Thus they express the relationship between various frequency banks from a quantitative manner. Therefore, combining the wavelet scalogram and amplitude spectrum when making analysis, as they complement and verify each other, it will enhance the reliability when extract and analyze the characteristics of fault signal.

Robust estimation of instantaneous phase using a time-frequency adaptive filter

Geophysics ◽  
2013 ◽  
Vol 78 (1) ◽  
pp. O1-O7 ◽  
Author(s):  
Wen-kai Lu ◽  
Chang-Kai Zhang
Keyword(s):  
Adaptive Filter ◽  
Signal To Noise Ratio ◽  
Amplitude Spectrum ◽  
Estimation Method ◽  
Frequency Component ◽  
Data Sets ◽  
Time Frequency ◽  
Instantaneous Phase ◽  
The Hilbert Transform ◽  
Short Time

The instantaneous phase estimated by the Hilbert transform (HT) is susceptible to noise; we propose a robust approach for the estimation of instantaneous phase in noisy situations. The main procedure of the proposed method is applying an adaptive filter in time-frequency domain and calculating the analytic signal. By supposing that one frequency component with higher amplitude has higher signal-to-noise ratio, a zero-phase adaptive filter, which is constructed by using the time-frequency amplitude spectrum, enhances the frequency components with higher amplitudes and suppresses those with lower amplitudes. The estimation of instantaneous frequency, which is defined as the derivative of instantaneous phase, is also improved by the proposed robust instantaneous phase estimation method. Synthetic and field data sets are used to demonstrate the performance of the proposed method for the estimation of instantaneous phase and frequency, compared by the HT and short-time-Fourier-transform methods.

scholarly journals FREQUENCY COMPONENT EXTRACTION OF HEARTBEAT CUES WITH SHORT TIME FOURIER TRANSFORM (STFT)

2017 ◽  
Vol 5 (1) ◽  
pp. 1 ◽  
Author(s):  
Sumarna Sumarna ◽  
Agus Purwanto ◽  
Dyah Kurniawati Agustika
Keyword(s):  
Fourier Transform ◽  
Frequency Spectrum ◽  
Bandpass Filter ◽  
Frequency Component ◽  
Analysis Program ◽  
Short Time Fourier Transform ◽  
Matlab Program ◽  
Frequency Components ◽  
Short Time ◽  
Spectrum Graph

Abstract Electro-acoustic human heartbeat detector have been made with the main parts : (a) stetoscope (piece chest), (b) mic condenser, (c) transistor amplifier, and (d) cues analysis program with MATLAB. The frequency components that contained in heartbeat. cues have also been extracted with Short Time Fourier Transform (STFT) from 9 volunteers. The results of the analysis showed that heart rate appeared in every cue frequency spectrum with their harmony. The steps of the research were including detector instrument design, test and instrument repair, cues heartbeat recording with Sound Forge 10 program and stored in wav file ; cues breaking at the start and the end, and extraction/cues analysis using MATLAB. The MATLAB program included filter (bandpass filter with bandwidth between 0.01 – 110 Hz), cues breaking with hamming window and every part was calculated using Fourier Transform (STFT mechanism) and the result were shown in frequency spectrum graph. Keywords: frequency components extraction, heartbeat cues, Short Time Fourier Transform

A Harmonic Tracking Technique for Recovery of Gear Motion From Non-Stationary Vibration Signals

1995 ◽  
Author(s):  
Christopher A. Lerch ◽  
Richard H. Lyon
Keyword(s):  
Diagnostic System ◽  
Time Spectrum ◽  
Time Dependent ◽  
Invasive Technique ◽  
Signal Distortion ◽  
Vibration Signals ◽  
Tracking Method ◽  
Non Invasive ◽  
Stationary Vibration ◽  
Short Time

Abstract A method termed harmonic tracking is developed to recover time dependent gear motion from machine casing vibration. The harmonic tracking method uses short-time spectral generation and a subsequent set of algorithms to locate and track gear meshing frequencies as functions of time. The meshing frequencies are then integrated with respect to time to obtain the rotation of individual gears. More specifically, spectral generation is performed using the discrete Fourier transform, and the locating and tracking algorithms involve locating tones in each short-time spectrum and tracking them through successive spectra to recover gear meshing harmonics. The harmonic tracking method is found to be more robust than demodulation-based methods in the presence of measurement noise and signal distortion from the structural transfer function between gears and the casing. The harmonic tracking method is tested, both through simulation and experiments involving motor-operated valves (MOV’s) as part of the development of a diagnostic system for MOV’s. In all cases, the harmonic tracking method is found to recover gear motion with sufficient accuracy to perform diagnostics. The harmonic tracking method should be generally applicable to situations in which a non-invasive technique is required for determining the time-dependent angular speeds and displacements of gearbox input, intermediary, and output shafts.

Gentrification, displacement and the arts: Untangling the relationship between arts industries and place change

Urban Studies ◽  
2016 ◽  
Vol 55 (4) ◽  
pp. 807-825 ◽  
Author(s):  
Carl Grodach ◽  
Nicole Foster ◽  
James Murdoch
Keyword(s):  
Urban Policy ◽  
Statistical Study ◽  
Change Agents ◽  
Creative Industries ◽  
Standard Account ◽  
Clear Cut ◽  
The Arts ◽  
Neighbourhood Level ◽  
The Relationship

The arts have long played a role in debates around gentrification and displacement, yet their roles and impacts as change agents are not clear-cut. According to the standard account, artists facilitate gentrification and ultimately engender the displacement of lower income households, but more recent research complicates the accepted narrative. This article seeks to untangle the relationship between the arts, gentrification and displacement through a statistical study of neighbourhood-level arts industry activity within large US regions. The findings indicate that the standard arts-led gentrification narrative is too generalised or simply no longer applicable to contemporary arts-gentrification processes. Rather, the arts have multiple, even conflicting relationships with gentrification and displacement that depend on context and type of art. These results have important implications for how we study the role of the arts in neighbourhood change and for how governments approach the arts and creative industries in urban policy.

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