### Abstract

We propose an adaptive quadratic time-frequency representation (QTFR) based on a matching pursuit signal decomposition that uses a dictionary with elements matched to the instantaneous frequency of the analysis signal components. We form the QTFR as a weighted linear superposition of QTFRs chosen by the algorithm to provide a highly localized representation for each of the adaptively selected dictionary elements. This is advantageous as the resulting representations are parsimonious and reduce the effect of cross terms. Also, they exhibit maximum time-frequency localization for the difficult analysis case of signals with multiple components that have different time-frequency characteristics. Thus, the new technique can be used to analyze and classify multi-structure signal components as demonstrated by our synthetic and real data simulation examples.

Original language | English (US) |
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Title of host publication | IEEE Signal Processing Workshop on Statistical Signal and Array Processing, SSAP |

Place of Publication | Los Alamitos, CA, United States |

Publisher | IEEE |

Pages | 579-583 |

Number of pages | 5 |

State | Published - 2000 |

Event | Proceedings of the 10th IEEE Workshop on Statiscal and Array Processing - Pennsylvania, PA, USA Duration: Aug 14 2000 → Aug 16 2000 |

### Other

Other | Proceedings of the 10th IEEE Workshop on Statiscal and Array Processing |
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City | Pennsylvania, PA, USA |

Period | 8/14/00 → 8/16/00 |

### Fingerprint

### ASJC Scopus subject areas

- Engineering(all)

### Cite this

*IEEE Signal Processing Workshop on Statistical Signal and Array Processing, SSAP*(pp. 579-583). Los Alamitos, CA, United States: IEEE.

**Adaptive time-frequency representations for multiple structures.** / Papandreou-Suppappola, Antonia; Suppappola, Seth B.

Research output: Chapter in Book/Report/Conference proceeding › Chapter

*IEEE Signal Processing Workshop on Statistical Signal and Array Processing, SSAP.*IEEE, Los Alamitos, CA, United States, pp. 579-583, Proceedings of the 10th IEEE Workshop on Statiscal and Array Processing, Pennsylvania, PA, USA, 8/14/00.

}

TY - CHAP

T1 - Adaptive time-frequency representations for multiple structures

AU - Papandreou-Suppappola, Antonia

AU - Suppappola, Seth B.

PY - 2000

Y1 - 2000

N2 - We propose an adaptive quadratic time-frequency representation (QTFR) based on a matching pursuit signal decomposition that uses a dictionary with elements matched to the instantaneous frequency of the analysis signal components. We form the QTFR as a weighted linear superposition of QTFRs chosen by the algorithm to provide a highly localized representation for each of the adaptively selected dictionary elements. This is advantageous as the resulting representations are parsimonious and reduce the effect of cross terms. Also, they exhibit maximum time-frequency localization for the difficult analysis case of signals with multiple components that have different time-frequency characteristics. Thus, the new technique can be used to analyze and classify multi-structure signal components as demonstrated by our synthetic and real data simulation examples.

AB - We propose an adaptive quadratic time-frequency representation (QTFR) based on a matching pursuit signal decomposition that uses a dictionary with elements matched to the instantaneous frequency of the analysis signal components. We form the QTFR as a weighted linear superposition of QTFRs chosen by the algorithm to provide a highly localized representation for each of the adaptively selected dictionary elements. This is advantageous as the resulting representations are parsimonious and reduce the effect of cross terms. Also, they exhibit maximum time-frequency localization for the difficult analysis case of signals with multiple components that have different time-frequency characteristics. Thus, the new technique can be used to analyze and classify multi-structure signal components as demonstrated by our synthetic and real data simulation examples.

UR - http://www.scopus.com/inward/record.url?scp=0033676388&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0033676388&partnerID=8YFLogxK

M3 - Chapter

AN - SCOPUS:0033676388

SP - 579

EP - 583

BT - IEEE Signal Processing Workshop on Statistical Signal and Array Processing, SSAP

PB - IEEE

CY - Los Alamitos, CA, United States

ER -