stationary signals
Time Frequency Domain Characterization of Stationary and Non stationary Signals
... The Fig. 3 shows the Fourier transform of the signals Type I- IV. From the figure it is quite clear the Fourier transforms fails to provide the precise value of the frequency present in the signal. This is due to ...
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DOA Estimation of Quasi-Stationary Signals Using a Partly-Calibrated Uniform Linear Array with Fewer Sensors Than Sources
... quasi-stationary signals with a partly-calibrated ...source signals to estimate their ...source signals with N sensors, which is the maximum achievable degree-of ...
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Grade Nested Array with Increased Degrees of Freedom for Quasi-Stationary Signals
... The DOAs of six narrowband uncorrelated quasi-stationary signals are [ − 50 ◦ , − 40 ◦ , − 30 ◦ , − 20 ◦ , 30 ◦ , 40 ◦ ]. Let T = 500, Q = 40 and L = 7, and the RMSEs with respect to the SNR are described ...
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Feature Extraction Techniques of Non Stationary Signals for Fault Diagnosis in Machinery Systems
... non-stationary signals, and the signal features must be averaged with analysis time which makes it difficult to identify the causes of ...non-stationary signals of gear- rotor ...
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Discrete Time Frequency Signal Analysis and Processing Techniques for Non Stationary Signals
... Non-stationary signals comprise of mono component or ...non-stationary signals or time-varying ...non-stationary signals for joint time-frequency ...
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The Enhanced Ensemble Empirical Mode Decomposition for Analyzing Non Linear and Non Stationary Signals K Ganga Bhavani, T. Durga Rao
... Empirical Mode Decomposition (EMD) [1] is an adaptive algorithm used for analysis of non-linear and non-stationary signals. It works by breaking the signal in to a number of amplitude and frequency ...
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Time-Frequency Domain Characterization of Stationary and Non stationary Signals
... of signals for the stationary as well as non-stationary ...the signals, it has been always a challenge to achieve time frequency distribution of such ...of stationary as well as ...
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Classification of non stationary signals using multiscale decomposition
... superimposed signals correspond to short potentials or artifacts which appear randomly throughout the signal, such as foetus motions, Alvarez waves and other superimposed events ...
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Non Stationary Signals (Voice) Verification System Using Wavelet Transform PPS Subhashini, Dr M Satya Sairam & Dr D Srinivasa Rao
... Speech recognition (SR) is the inter-disciplinary sub- field of computational linguistics which incorporates knowledge and research in the linguistics, computer science, and electrical engineering fields to develop ...
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A methodology for time-frequency image processing applied to the classification of non-stationary multichannel signals using instantaneous frequency descriptors with application to newborn EEG signals
... non-stationary signals for the purpose of classification and ...EEG signals in a multichannel-based newborn EEG seizure detection for the purpose of localizing EEG abnormalities on the ...
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Modified EMD with double density wavelet based machinery abnormality detection
... fault signals for machinery rotating motor ...false signals and false frequency occurrence, while processing the vibration signal, the time and frequency domain has been widely using in the rotating ...
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Parametric Time-Frequency Analysis and Its Applications in Music Classification
... real-world signals are non-stationary, the study and analysis of non-stationary signals is receiving more and more attention in the scientific ...of signals. But by themselves, the best ...
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Evaluation of the modified S-transform for time-frequency synchrony analysis and source localisation
... time-frequency distribution (TFD) is used to analyze and process non-stationary signals in the joint time-fre- quency domain. Several TFDs exist in the literature [1]. Most of them are based on the ...
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Decomposition of 3D medical image based on Fast and Adaptive Bidimensional Empirical Mode Decomposition
... Three-dimensional (3D) imaging and display have been subjects of much research due to their diverse benefits and applications. This paper presents a new approach for decomposing the three-dimensional medical images using ...
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Localization of Phase Spectrum Using Modified Continuous Wavelet Transform
... Signal processing has played an important role in different engineering applications. Early developments have treated image processing as more of arts than science, but with the time, recent algorithms for different ...
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Non Stationary Power Quality Signals Classification using Fuzzy C means Algorithm
... non-stationary signals, the STFT does not track the signal dynamics properly due to the limitations of a fixed window width chosen a ...power signals are usually non–stationary, this on-line ...
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The analysis of transient signals and stationary noise
... a stationary stochastic process, it is often the case that these techniques are applied to some types of non stationary data because there is no alternative more ...
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Cyclo Stationary Based Spectrum Sensing of Interleaved SC FDMA Signals
... Comments: Let us consider the case of all the users are transmitting and SOI is obtained by filtering. In doing so, the frequency components of the unwanted users are eliminated. As we discussed already an increase in M ...
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RECOVERY OF EMG SIGNALS FROM THE MIXTURE OF ECG-EMG SIGNALS USING NON-STATIONARY HARMONIC MODELING
... real-world signals, show that in the analysis bandwidth 0–20 Hz, the proposed method outperforms the reference methods, as it introduces the smallest distortion in the EMG signal ...
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Stationary and non-stationary solutions of the evolution equation for neutrino in matter
... the stationary states and the spin-flavor coherent states of the neutrino are ...the stationary states with coefficients, which depend on the mixing angle in ...
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