Computationally Efficient Estimation of Multi-dimensional Damped Modes using Sparse Wideband Dictionaries*

Computationally Efficient Estimation of Multi-dimensional Damped Modes using Sparse Wideband Dictionaries*. Jälmby, M., Swärd, J., Elvander, F., & Jakobsson, A. In 2018 26th European Signal Processing Conference (EUSIPCO), pages 1745-1749, Sep., 2018.
doi abstract bibtex

Estimating the parameters of non-uniformly sampled multi-dimensional damped modes is computationally cumbersome, especially if the model order of the signal is not assumed to be known a priori. In this work, we examine the possibility of using the recently introduced wideband dictionary framework to formulate a computationally efficient estimator that iteratively refines the estimates of the candidate frequency and damping coefficients for each component. The proposed wideband dictionary allows for the use of a coarse initial grid without increasing the risk of not identifying closely spaced components, resulting in a substantial reduction in computational complexity. The performance of the proposed method is illustrated using both simulated and real spectroscopy data, clearly showing the improved performance as compared to previous techniques.

@InProceedings{8553460,
  author = {M. Jälmby and J. Swärd and F. Elvander and A. Jakobsson},
  booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)},
  title = {Computationally Efficient Estimation of Multi-dimensional Damped Modes using Sparse Wideband Dictionaries*},
  year = {2018},
  pages = {1745-1749},
  abstract = {Estimating the parameters of non-uniformly sampled multi-dimensional damped modes is computationally cumbersome, especially if the model order of the signal is not assumed to be known a priori. In this work, we examine the possibility of using the recently introduced wideband dictionary framework to formulate a computationally efficient estimator that iteratively refines the estimates of the candidate frequency and damping coefficients for each component. The proposed wideband dictionary allows for the use of a coarse initial grid without increasing the risk of not identifying closely spaced components, resulting in a substantial reduction in computational complexity. The performance of the proposed method is illustrated using both simulated and real spectroscopy data, clearly showing the improved performance as compared to previous techniques.},
  keywords = {computational complexity;damping;gradient methods;iterative methods;parameter estimation;signal sampling;damping coefficients;computational complexity;computationally efficient estimation;multidimensional damped modes;sparse wideband dictionaries;nonuniformly sampled multidimensional;recently introduced wideband dictionary framework;computationally efficient estimator;candidate frequency;Dictionaries;Frequency estimation;Wideband;Damping;Hypercubes;Estimation;Computational complexity;Sparse signal analysis;dictionary learning;damped sinusoids;wideband dictionaries},
  doi = {10.23919/EUSIPCO.2018.8553460},
  issn = {2076-1465},
  month = {Sep.},
}

Downloads: 0

{"_id":"3zGkS7M2me3pn8RAy","bibbaseid":"jlmby-swrd-elvander-jakobsson-computationallyefficientestimationofmultidimensionaldampedmodesusingsparsewidebanddictionaries-2018","authorIDs":[],"author_short":["Jälmby, M.","Swärd, J.","Elvander, F.","Jakobsson, A."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"firstnames":["M."],"propositions":[],"lastnames":["Jälmby"],"suffixes":[]},{"firstnames":["J."],"propositions":[],"lastnames":["Swärd"],"suffixes":[]},{"firstnames":["F."],"propositions":[],"lastnames":["Elvander"],"suffixes":[]},{"firstnames":["A."],"propositions":[],"lastnames":["Jakobsson"],"suffixes":[]}],"booktitle":"2018 26th European Signal Processing Conference (EUSIPCO)","title":"Computationally Efficient Estimation of Multi-dimensional Damped Modes using Sparse Wideband Dictionaries*","year":"2018","pages":"1745-1749","abstract":"Estimating the parameters of non-uniformly sampled multi-dimensional damped modes is computationally cumbersome, especially if the model order of the signal is not assumed to be known a priori. In this work, we examine the possibility of using the recently introduced wideband dictionary framework to formulate a computationally efficient estimator that iteratively refines the estimates of the candidate frequency and damping coefficients for each component. The proposed wideband dictionary allows for the use of a coarse initial grid without increasing the risk of not identifying closely spaced components, resulting in a substantial reduction in computational complexity. The performance of the proposed method is illustrated using both simulated and real spectroscopy data, clearly showing the improved performance as compared to previous techniques.","keywords":"computational complexity;damping;gradient methods;iterative methods;parameter estimation;signal sampling;damping coefficients;computational complexity;computationally efficient estimation;multidimensional damped modes;sparse wideband dictionaries;nonuniformly sampled multidimensional;recently introduced wideband dictionary framework;computationally efficient estimator;candidate frequency;Dictionaries;Frequency estimation;Wideband;Damping;Hypercubes;Estimation;Computational complexity;Sparse signal analysis;dictionary learning;damped sinusoids;wideband dictionaries","doi":"10.23919/EUSIPCO.2018.8553460","issn":"2076-1465","month":"Sep.","bibtex":"@InProceedings{8553460,\n author = {M. Jälmby and J. Swärd and F. Elvander and A. Jakobsson},\n booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)},\n title = {Computationally Efficient Estimation of Multi-dimensional Damped Modes using Sparse Wideband Dictionaries*},\n year = {2018},\n pages = {1745-1749},\n abstract = {Estimating the parameters of non-uniformly sampled multi-dimensional damped modes is computationally cumbersome, especially if the model order of the signal is not assumed to be known a priori. In this work, we examine the possibility of using the recently introduced wideband dictionary framework to formulate a computationally efficient estimator that iteratively refines the estimates of the candidate frequency and damping coefficients for each component. The proposed wideband dictionary allows for the use of a coarse initial grid without increasing the risk of not identifying closely spaced components, resulting in a substantial reduction in computational complexity. The performance of the proposed method is illustrated using both simulated and real spectroscopy data, clearly showing the improved performance as compared to previous techniques.},\n keywords = {computational complexity;damping;gradient methods;iterative methods;parameter estimation;signal sampling;damping coefficients;computational complexity;computationally efficient estimation;multidimensional damped modes;sparse wideband dictionaries;nonuniformly sampled multidimensional;recently introduced wideband dictionary framework;computationally efficient estimator;candidate frequency;Dictionaries;Frequency estimation;Wideband;Damping;Hypercubes;Estimation;Computational complexity;Sparse signal analysis;dictionary learning;damped sinusoids;wideband dictionaries},\n doi = {10.23919/EUSIPCO.2018.8553460},\n issn = {2076-1465},\n month = {Sep.},\n}\n\n","author_short":["Jälmby, M.","Swärd, J.","Elvander, F.","Jakobsson, A."],"key":"8553460","id":"8553460","bibbaseid":"jlmby-swrd-elvander-jakobsson-computationallyefficientestimationofmultidimensionaldampedmodesusingsparsewidebanddictionaries-2018","role":"author","urls":{},"keyword":["computational complexity;damping;gradient methods;iterative methods;parameter estimation;signal sampling;damping coefficients;computational complexity;computationally efficient estimation;multidimensional damped modes;sparse wideband dictionaries;nonuniformly sampled multidimensional;recently introduced wideband dictionary framework;computationally efficient estimator;candidate frequency;Dictionaries;Frequency estimation;Wideband;Damping;Hypercubes;Estimation;Computational complexity;Sparse signal analysis;dictionary learning;damped sinusoids;wideband dictionaries"],"metadata":{"authorlinks":{}},"downloads":0},"bibtype":"inproceedings","biburl":"https://raw.githubusercontent.com/Roznn/EUSIPCO/main/eusipco2018url.bib","creationDate":"2021-02-13T15:38:40.449Z","downloads":0,"keywords":["computational complexity;damping;gradient methods;iterative methods;parameter estimation;signal sampling;damping coefficients;computational complexity;computationally efficient estimation;multidimensional damped modes;sparse wideband dictionaries;nonuniformly sampled multidimensional;recently introduced wideband dictionary framework;computationally efficient estimator;candidate frequency;dictionaries;frequency estimation;wideband;damping;hypercubes;estimation;computational complexity;sparse signal analysis;dictionary learning;damped sinusoids;wideband dictionaries"],"search_terms":["computationally","efficient","estimation","multi","dimensional","damped","modes","using","sparse","wideband","dictionaries","jälmby","swärd","elvander","jakobsson"],"title":"Computationally Efficient Estimation of Multi-dimensional Damped Modes using Sparse Wideband Dictionaries*","year":2018,"dataSources":["yiZioZximP7hphDpY","iuBeKSmaES2fHcEE9"]}