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[PDF] Top 20 Sparse Time-Frequency Data Analysis: A Multi-Scale Approach

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Sparse Time-Frequency Data Analysis: A Multi-Scale Approach

Sparse Time-Frequency Data Analysis: A Multi-Scale Approach

... This approach helps us to find a sparser representation compared to the case in which one uses a normal envelope dictionary ...the time-frequency domain, the reduction of the parameter λ is always ... See full document

197

Multi-frequency scale Gaussian regression for noisy time-series data

Multi-frequency scale Gaussian regression for noisy time-series data

... to time-series data analysis. To extract from the data separate components with different frequency scales, the Gaussian regression methodology is extended through the use of multiple ... See full document

6

Multi-scale Jump and Volatility Analysis for. High-Frequency Financial Data

Multi-scale Jump and Volatility Analysis for. High-Frequency Financial Data

... based multi-scale approach to perform efficient jump and volatility analysis for high-frequency ...handle data with both microstructure noise and jumps in prices, providing ... See full document

40

Data-driven time-frequency analysis of multivariate data

Data-driven time-frequency analysis of multivariate data

... real-world multi-exposure images shown in Figure ...a multi-resolution wavelet-based fusion scheme is also used: the Discrete Wavelet transform (DWT) was first applied to both input images to obtain their ... See full document

169

Multi-scale Sparse Coding With Anomaly Detection And Classification

Multi-scale Sparse Coding With Anomaly Detection And Classification

... standard sparse error-coding frame- work is that anomalies at all scales are treated the ...the data. The wavelet transform is a multi-scale time-frequency transform that with ... See full document

5

Time-scale and memory in financial time series: a data mining approach

Time-scale and memory in financial time series: a data mining approach

... Financial time series analysis is a highly empirical discipline concerned with the evo- lution of the price of an ...financial time series from time series of other scientific domains is the ... See full document

239

Multi-Scale Approach for the Electromagnetic Simulation of Finite Size and Thick Frequency Selective Surfaces

Multi-Scale Approach for the Electromagnetic Simulation of Finite Size and Thick Frequency Selective Surfaces

... wide frequency band under an oblique incidence plane wave ...computation time is significantly reduced when using SCT-based software compared with the FEM simulation ...full-wave analysis tools that ... See full document

15

Frequency-splitting Dynamic MRI Reconstruction using Multi-scale 3D Convolutional Sparse Coding and Automatic Parameter Selection

Frequency-splitting Dynamic MRI Reconstruction using Multi-scale 3D Convolutional Sparse Coding and Automatic Parameter Selection

... learning approach, can be adapted to features from input data by training ...of time-axis. Efficient convolutional sparse coding (CSC) is then introduced by minimizing an energy objective ... See full document

48

Multi-scale analysis of linear data in a two-dimensional space

Multi-scale analysis of linear data in a two-dimensional space

... alternative approach to represent time series and overcomes the difficulty of traditional approaches in visualising time series at multiple ...of time intervals initially proposed by Kulpa 12, ... See full document

21

Frequency domain analysis and simulation of multi-channel complex-valued time series

Frequency domain analysis and simulation of multi-channel complex-valued time series

... estimation approach utilizing K data taper sequences, for a finite K, is ...recorded data set. It would be interesting to extend the analysis to a bivariate complex-valued time series, ... See full document

207

MULTI-SCALE SPARSE DOMINATION

MULTI-SCALE SPARSE DOMINATION

... In the general case we replace the couple of pairs (S B 1 , S B 2 ∗ ) and (L p , L p 0 ) by the couple of pairs (V 1 , V 2 ) and (L p , L p 0 ) and see that a repetition of the above arguments settles this case as well. ... See full document

93

Global Testing Against Sparse Alternatives in Time-Frequency Analysis

Global Testing Against Sparse Alternatives in Time-Frequency Analysis

... 4. Discussion. Motivated by periodicity detection in complex-valued time series analysis, we investigated the hypothesis testing problem (1.6) under the linear model (1.4), where the frequencies of the ... See full document

32

Time Domain Sparse Representation for Multi-Aspect SAR Data of Targets

Time Domain Sparse Representation for Multi-Aspect SAR Data of Targets

... TD sparse representation has advantages in avoiding noise ...measured data in the solving ...the sparse representation, we have to search the solution that makes Δ = || d − Ys || 2 2 + λ || s || 1 ... See full document

8

Data envelopment analysis of clinics with sparse data: fuzzy clustering approach

Data envelopment analysis of clinics with sparse data: fuzzy clustering approach

... each time to determine the best set of weights which maximize the efficiency of the DMU under evaluation, while the weights should remain feasible for all the other ... See full document

25

Commodity dynamics: a sparse multi-class approach

Commodity dynamics: a sparse multi-class approach

... A Sparse Multi-class Approach Luca Barbaglia ∗ , Ines Wilms, and Christophe Croux KU Leuven, Faculty of Economics and Business ...a sparse estimator of the Multi-class Vector ... See full document

23

Image classification based on sparse coding multi-scale spatial latent semantic analysis

Image classification based on sparse coding multi-scale spatial latent semantic analysis

... on sparse coding and multi-scale spatial latent se- mantic analysis is ...generate multi-scale spatial latent se- mantic information with high classification ... See full document

11

Densification of spatially-sparse legacy soil data at a national scale: a digital mapping approach

Densification of spatially-sparse legacy soil data at a national scale: a digital mapping approach

... soil data because most soil properties exhibit high variability over short distances, so much that the skills and expertise necessary to accurately record, measure and map such changes are prohibitive in terms of ... See full document

253

Time-frequency Signature Sparse Reconstruction using Chirp Dictionary

Time-frequency Signature Sparse Reconstruction using Chirp Dictionary

... in sparse signal reconstruction for IF estimation for chirp signals and MicroDoppler ...dictionary approach may give inaccurate TF signal reconstruction due to violation of chirp piece-wise approximation of ... See full document

9

Hybrid sparse and low-rank time-frequency signal decomposition

Hybrid sparse and low-rank time-frequency signal decomposition

... short- time Fourier transform), that are naturally defined in the complex-valued domain though they are commonly used for the representation of real-valued ... See full document

6

Sparse Multi Scale Grammars for Discriminative Latent Variable Parsing

Sparse Multi Scale Grammars for Discriminative Latent Variable Parsing

... train multi- scale grammars of increasing latent complexity as described in Section 5, directly incorporating the additional features from Section 6 into the training ...testing time we marginalize ... See full document

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