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Murat Akçakaya

5 accepted papers

2020

Clutter Identification Based on Sparse Recovery and L1-Type Probabilistic Distance Measures

ICASSP 2020accepted

Cognitive radar framework has recently been proposed in radar signal processing to develope algorithms for target detection, tracking, and waveform design in the presence of nonstationary environmental (clutter) characteristics. In this framework, there are the three main steps: sensing the environm…

Cited by 0SourceScholar
2019

A History-based Stopping Criterion in Recursive Bayesian State Estimation

ICASSP 2019accepted

In dynamic state-space models, the state can be estimated through recursive computation of the posterior distribution of the state given all measurements. In scenarios where active sensing/querying is possible, a hard decision is made when the state posterior achieves a pre-set confidence threshold.…

Cited by 0SourceScholar
2019

Bhattacharyya Distance-based Transfer Learning for a Hybrid EEG-FTCD Brain-computer Interface

ICASSP 2019accepted

In this paper, we introduce a transfer learning approach for our novel hybrid brain-computer interface in which electroencephalography and functional transcranial Doppler ultrasound are used simultaneously to record brain electrical activity and cerebral blood velocity respectively due to flickering…

Cited by 0SourceScholar
2017

Decoding emotional experiences through physiological signal processing

ICASSP 2017accepted

All modern emotion theoretical views assume a role for peripheral physiological changes during emotional experiences. In this paper, we explored the correlation between autonomically-mediated changes in multimodal bodily signals and discrete emotional states. In order to fully exploit the informatio…

Cited by 0SourceScholar
2017

Transfer learning for EEG based BCI using LEARN++.NSE and mutual information

ICASSP 2017accepted

In this paper, the use of mutual information and the Learn++.NSE algorithm is proposed to create an EEG SSVEP BCI system that can select and utilize data sets originating from a group of users. In typical BCI systems, the nonstationarity in the EEG prevents the system from blindly applying training…

Cited by 0SourceScholar