[PDF] Top 20 Spectral Density Estimation of Continuous Time Series
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Spectral Density Estimation of Continuous Time Series
... Although spectral analysis is one of the oldest tools for time series analysis, it is still one of the most widely used analysis techniques in many branches of sciences, ...stationary time ... See full document
9
The estimation of continuous-time systems using discrete data
... a continuous process it seems likely that one would sample with the intention of leaving a negligible spectral mass beyond the Nyquist ...economic series, for example, it may indeed be substantially ... See full document
161
Robust noise power spectral density estimation for binaural speech enhancement in time-varying diffuse noise field
... power spectral density (PSD) estimation plays a key role in determining appropriate de-nosing ...in time- varying noise ...in time-varying noise environments, an eigenvalue compensation ... See full document
16
Some aspects of time series frequency estimation
... S tudies of frequency e stim atio n freq u en tly focus on com parisons of different ty p es of e stim ate , for exam ple th e p erio d o g ram m ax im u m versus th e autoregressive or m ax im u m -en tro p y sp ec tra ... See full document
146
Sample space-time covariance matrix estimation
... the estimation links directly to previ- ously explored perturbation of the analytic eigenvalues and eigenspaces of a parahermitian cross-spectral density matrix when estimated from finite ... See full document
5
Fuzzy clustering of time series gene expression data with cubic spline
... spline estimation to represent gene time-series expression pro- files as continuous curves, by which noise can be filtered and meaningful data will be ... See full document
6
The Influence of Noise Uncertainty and SNR Wall on the Performance of Hybrid Sensing Method
... of spectral power density estimation and incorporating the effect of ‘SNR Wall’ leads to significant deterioration of the results, but still allows us to achieve better HD detection properties in ... See full document
7
The Time Series Spectral Analysis of Satellite Altimetry and Coastal Tide Gauges and Tide Modeling in the Coast of Caspian Sea
... squares’ spectral analysis is a modeling method for approximate behavior of natural and physical be- haviors ...power spectral density (PSD) that is a Fourier ...the spectral analy- sis method ... See full document
12
State-by-state Minimax Adaptive Estimation for Nonparametric Hidden Markov Models
... the density of three consecutive observations of the HMM using a least squares ...this density. In practice, these methods are more accurate than the spectral methods and are more stable when the ... See full document
46
Strip/Foil Rolling Mill Stochastic Excitation Model and Its Stability
... ARMA time series model and the stochastic excitation power spectral density (PSD) model are established, and the stochastic rolling forces excitation model is established by utilizing ... See full document
8
Spectral analysis of high dimensional time series
... the spectral density matrix is in esti- mating the frequency domain analog of the partial correlation structure, known as partial coherence, of the multivariate time ...High-dimensional time ... See full document
24
Robust estimation for structural time series models
... Kitagawa employs a direct method for his filter but a great deal of computation is required . This is especially true when we extend the filter to analyse models with multidimensional state . In this case , the system ... See full document
316
Estimation for vector linear time series models
... (or spectral equivalents to this likelihood) although Gaussianity is not required for any of the results to ...multiple time series and each model to be covered in the thesis is ...non-deterministic ... See full document
214
Recent advances on the semi-parametric estimation of the long-range dependence coefficient
... the spectral density at zero frequency, it is possible to estimate the rate of convergence to zero of the autocovariance coe- cients of the process for large lags (section ...the spectral ... See full document
14
Dimensionality reduction in nonparametric conditional density estimation with applications to nonlinear time series
... no estimation of smoothing parameter is involved ...each density estimate, and therefore it may stabilise the …nite-sample performances as it ensures that all density estimates are ...each ... See full document
153
Power Spectral Density Analysis of Time Series of Pixel of Functional Magnetic Resonance Image for Different Motor Activity
... Neurologists use fMRI, a powerful tool to study the function of the brain. fMRI is a diagnostic method used to study the working of a normal, diseased or injured brain. Risk after neuro surgery or invasive treatment is ... See full document
8
Nonlinear Interaction of Electromagnetic Radiation at the Cell Membrane Level: Response to Stochastic Fields
... first time to the best of our knowledge, the Volterra series formalism was used to derive the power spectral density of the transmembrane potential response in a spherical cell with nonlinear ... See full document
23
An Updated Literature Review of Distance Correlation and Its Applications to Time Series
... multivariate time series at a fixed ...generalized spectral domain following Hong’s (1999) ...in time series can be characterized by the generalized spectral density ... See full document
37
Estimation of Fractal Dimension of a Noisy Time Series
... To estimate a best possible value of embedding dimension m is to check for the closed false neighbors (FNN) in the trajectory of phase space at different value of m [10]. Kennel et al., [10] developed an algorithm that ... See full document
6
Vector exponential time series modeling for polynomial J spectral factorization
... Remark 6: As mentioned in the introduction to the previ- ous section, in the illustration of out results we have decided to concentrate on a special case for ease of exposition. Observe for instance that in Example 5 we ... See full document
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