Maria Sandsten
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- 2020
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Mark
A multitaper reassigned spectrogram for increased time-frequency localization precision
2020) IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2020 p.5310-5314(
- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding
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Mark
The matched reassigned cross-spectrogram for phase estimation
2020) IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2020 p.5960-5964(
- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding
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Mark
Time-frequency feature extraction for classification of episodic memory
2020) In Eurasip Journal on Advances in Signal Processing(
- Contribution to journal › Article
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Mark
Multitaper Spectral Granger Causality with Application to Ssvep
2020) IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2020 p.1284-1288(
- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding
- 2019
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Mark
Inference for time-varying signals using locally stationary processes
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- Contribution to journal › Article
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Mark
Efficient Thomson Spectral Estimator with Time-shifted Windows
2019) 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 2019-May. p.4983-4987(
- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding
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Mark
Detailed analysis of two detected overlaying transient components within the echolocation beam of a bottlenose dolphin (Tursiops truncatus)
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- Contribution to journal › Article
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Mark
Stochastic Modeling and Optimal Time-Frequency Estimation of Task-Related HRV
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- Contribution to journal › Article
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Mark
The matched reassignment applied to echolocation data
2019) IEEE International Conference on Acoustics, Speech, and Signal Processing 2019 In Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing. p.8236-8240(
- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding
- 2018
-
Mark
Classification of EEG signals based on mean-square error optimal time-frequency features
(
- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding