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Recent advances and applications of time-frequency signal analysis

  1. In this paper, we present a joint time-variant carrier frequency offset (CFO) and frequency-selective channel response estimation scheme for multiple input-multiple output-orthogonal frequency-division multipl...

    Authors: Nan-Hung Cheng, Kai-Chieh Huang, Yung-Fang Chen and Shu-Ming Tseng
    Citation: EURASIP Journal on Advances in Signal Processing 2021 2021:6
  2. This paper presents a novel type of a filter bank for image decomposition that incorporates “singular spectrum analysis” (SSA). SSA is based on “singular value decomposition” (SVD).The presented filter banks p...

    Authors: Julia Evers, Florian Evers, Florian Goppelt and Ronald Schmidt-Vollus
    Citation: EURASIP Journal on Advances in Signal Processing 2020 2020:29
  3. This paper focuses on a low-complexity one-dimensional (1D) direction-of-arrival (DOA) algorithm with an arbitrary cross-linear array. This algorithm is highly accurate without the performance error usually ca...

    Authors: Gengxin Ning, Guangyu Jing, Xiaopeng Li and Xuejin Zhao
    Citation: EURASIP Journal on Advances in Signal Processing 2020 2020:28
  4. The paper proposes a novel approach for extraction of useful information and blind source separation of signal components from noisy data in the time-frequency domain. The method is based on the local Rényi en...

    Authors: Ana Vranković, Jonatan Lerga and Nicoletta Saulig
    Citation: EURASIP Journal on Advances in Signal Processing 2020 2020:18
  5. The separation of overlapping components is a well-known and difficult problem in multicomponent signals analysis and it is shared by applications dealing with radar, biosonar, seismic, and audio signals. In o...

    Authors: Vittoria Bruni, Michela Tartaglione and Domenico Vitulano
    Citation: EURASIP Journal on Advances in Signal Processing 2020 2020:13
  6. The brain dynamics in the electroencephalogram (EEG) data are often challenging to interpret, specially when the signal is a combination of desired brain dynamics and noise. Thus, in an EEG signal, anything ot...

    Authors: Guruprasad Madhale Jadav, Jonatan Lerga and Ivan Štajduhar
    Citation: EURASIP Journal on Advances in Signal Processing 2020 2020:7
  7. Root tracking is a powerful technique that provides insight into the mechanisms of various time-varying processes. The poles and the zeros of a signal-generating system determine the spectral characteristics o...

    Authors: Kyriaki Kostoglou and Michael Lunglmayr
    Citation: EURASIP Journal on Advances in Signal Processing 2020 2020:6
  8. This work proposes an analog implementation of gradient-based algorithm for compressive sensing signal reconstruction. Compressive sensing has appeared as a promising technique for efficient acquisition and re...

    Authors: Irena Orović, Nedjeljko Lekić, Marko Beko and Srdjan Stanković
    Citation: EURASIP Journal on Advances in Signal Processing 2019 2019:61
  9. In this paper, the problem of detection of small signal-to-noise ratio (SNR) variations in noisy signals is addressed in order to provide an efficient and fast method for detection of faulty electroencephalogr...

    Authors: Zeljka Milanović, Nicoletta Saulig, Ivan Marasović and Damir Seršić
    Citation: EURASIP Journal on Advances in Signal Processing 2019 2019:38