@InProceedings{7362522,
  author = {F. Barzideh and K. Skretting and K. Engan},
  booktitle = {2015 23rd European Signal Processing Conference (EUSIPCO)},
  title = {The flexible signature dictionary},
  year = {2015},
  pages = {943-947},
  abstract = {Dictionary learning and Sparse representation of signals and images has been a hot topic for the past decade and aims to help find the sparsest representation for the signal(s) at hand. Typically, the Dictionary learning process involves finding a large number of free variables. Also, the resulting dictionary in general does not have a specific structure. In this paper we use the ideas from Image Signature Dictionary and General overlapping frames and proposed a flexible signature dictionary. We show that the resulting signatures capture the essence of the signal and can represent signals of their own type very well in opposed to signals of other types.},
  keywords = {image representation;general overlapping frames;image signature dictionary;sparse image representation;sparse signal representation;dictionary learning process;flexible signature dictionary;Dictionaries;Training;Signal processing algorithms;Noise measurement;Encoding;Europe;Signal processing;dictionary learning;signature dictionary;sparse representation},
  doi = {10.1109/EUSIPCO.2015.7362522},
  issn = {2076-1465},
  month = {Aug},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2015/papers/1570104751.pdf},
}

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