A NOVEL METHOD FOR SIGNAL COMPONENT INCISION IN THE TIME-FREQUENCY PLANE

Year 2010, Volume: 12 Issue: 3, 1 - 15, 01.10.2010

Yaşar Kemal Alp Orhan Arıkan Umut Özertem

Abstract

A new time-frequency signal analysis technique for detection and extraction of signal components, which
have non-overlapping compact support in the time-frequency plane, is developed. Proposed technique is
observed to be successful even under high noise levels. The method is composed of three main steps: 1)detection
of signal components, 2)estimation of instantaneous frequencies of the detected components 3) filtering in the
time-frequency plane. By construction, it is an iterative algorithm which detects and extracts one component at a
time. Time-frequency distributions are utilized for signal component detection and instantaneous frequency
estimation. Principle curve projections, which is very robust to noise, is used for instantaneous frequency
estimation. Filtering in the time-frequency plane is accomplished by frequency warping. The performance of the
proposed algorithm is analyzed on synthetic data sets for different noise levels

Keywords

Signal component, Time-frequency distribution, Instantaneous-frequency, Principle curve projections

ZAMAN-FREKANS DÜZLEMİNDE SİNYAL BİLEŞENİ ÇIKARIMI İÇİN YENİ BİR YÖNTEM

Abstract

have non-overlapping compact support in the time-frequency plane, is developed. Proposed technique is observed to be successful even under high noise levels. The method is composed of three main steps: 1)detection of signal components, 2)estimation of instantaneous frequencies of the detected components 3) filtering in the time-frequency plane. By construction, it is an iterative algorithm which detects and extracts one component at a time. Time-frequency distributions are utilized for signal component detection and instantaneous frequency estimation. Principle curve projections, which is very robust to noise, is used for instantaneous frequency estimation. Filtering in the time-frequency plane is accomplished by frequency warping. The performance of the proposed algorithm is analyzed on synthetic data sets for different noise levels

Keywords

Sinyal bileşeni, Zaman-frekans dağılımı, Anlık frekans, Ana eğri izdüşümleri

References

• Almeida L. B. (1994): “The Fractional Fourier Transform and Time-Frequency Representations”, IEEE Transactions on Signal Processing, Cilt 42, No. 11, s. 3084:3091.
• Boashash B. (19921): “Estimating and Interpreting the Instantaneous Frequency of a Signal- Part I: Fundementals”, Proceedings of IEEE, Cilt 80, No. 4, s. 520-538.
• Boashash B. (19922): “Estimating and Interpreting the Instantaneous Frequency of a Signal- Part II: Algorithms and Applications”, Proceedings of IEEE, Cilt 80, No. 4, s. 540-568.
• Cizek V. (1970): “Discrete Hilbert Transform”, IEEE Transactions on Audio and Electroacoustics, Cilt 18, No. 4, s. 340-343.
• Cohen L. (1989): “Time-Frequency Distribution- a Review”, Proceedings of IEEE, Cilt 77, No 7, s. 941-981.
• Cohen L. (1992): “What is a Multi-Component Signal”, IEEE International Conference on Acoustics, Speech and Signal Processing-ICASSP‟1992, Cilt 5, s. 113-1116.
• Daubechies I. (1990): “The Wavelet Transform, Time-Frequency Localization and Signal Analysis”, IEEE Transactions on Information Theory, Cilt. 36, No. 5, s. 961-1005.
• Erdoğmuş D., Özertem U. (2007): “Self-Consisted Locally Defined Principle Surfaces”, IEEE International Conference on Acoustics, Speech and Signal Processing-ICASSP‟2007, Cilt 2, s. 549-552.
• Mann S., Haykin S. (1995): “The Chirplet Tranform: Physical Considerations”, IEEE Transactions on Signal Processing, Cilt 43, No. 11, s. 2745-2761.
• Özdemir A. K. (2003): “Time-Frequency Component Analyzer”, Bilkent University Faculty of Engineering PhD Dissertation.
• Picinbono B. (1993): “On Instantaneous Amplitude and Phase of Signals”, IEEE Transactions on Signal Processing, Cilt 45, No. 3, s. 552-560.
• Qian S., Chen D. (1993): “Discrete Gabor Transform”, IEEE Transactions on Signal Processing, Cilt 41, No. 7, s. 2249-2438.