The Experts below are selected from a list of 921 Experts worldwide ranked by ideXlab platform
Peter Händel - One of the best experts on this subject based on the ideXlab platform.
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Unfolding the frequency spectrum for undersampled wideband data
Signal Processing, 2011Co-Authors: Charles Nader, Niclas Björsell, Peter HändelAbstract:In this letter, we discuss the problem of unfolding the frequency spectrum for undersampled wideband data. The problem is of relevance to state-of-the-art radio frequency measurement systems, which capture Repetitive Waveform based on a sampling rate that violates the Nyquist constraint. The problem is presented in a compact form by the inclusion of a complex operator called the CN operator. The ease-of-use problem formulation eliminates the ambiguity caused by folded frequency spectra, in particular those with lines standing on multiples of the Nyquist frequency that are captured with erroneous amplitude and phase values.
Thomas R Henry - One of the best experts on this subject based on the ideXlab platform.
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stereotyped high frequency oscillations discriminate seizure onset zones and critical functional cortex in focal epilepsy
Brain, 2018Co-Authors: Su Liu, Nerses Bebek, Candan Gurses, Altay Sencer, Zhiyi Sha, Michael M Quach, Daniel J Curry, Sujit S Prabhu, Sudhakar Tummala, Thomas R HenryAbstract:High-frequency oscillations in local field potentials recorded with intracranial EEG are putative biomarkers of seizure onset zones in epileptic brain. However, localized 80-500 Hz oscillations can also be recorded from normal and non-epileptic cerebral structures. When defined only by rate or frequency, physiological high-frequency oscillations are indistinguishable from pathological ones, which limit their application in epilepsy presurgical planning. We hypothesized that pathological high-frequency oscillations occur in a Repetitive fashion with a similar Waveform morphology that specifically indicates seizure onset zones. We investigated the Waveform patterns of automatically detected high-frequency oscillations in 13 epilepsy patients and five control subjects, with an average of 73 subdural and intracerebral electrodes recorded per patient. The Repetitive oscillatory Waveforms were identified by using a pipeline of unsupervised machine learning techniques and were then correlated with independently clinician-defined seizure onset zones. Consistently in all patients, the stereotypical high-frequency oscillations with the highest degree of Waveform similarity were localized within the seizure onset zones only, whereas the channels generating high-frequency oscillations embedded in random Waveforms were found in the functional regions independent from the epileptogenic locations. The Repetitive Waveform pattern was more evident in fast ripples compared to ripples, suggesting a potential association between Waveform repetition and the underlying pathological network. Our findings provided a new tool for the interpretation of pathological high-frequency oscillations that can be efficiently applied to distinguish seizure onset zones from functionally important sites, which is a critical step towards the translation of these signature events into valid clinical biomarkers.awx374media15721572971001.
Charles Nader - One of the best experts on this subject based on the ideXlab platform.
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Unfolding the frequency spectrum for undersampled wideband data
Signal Processing, 2011Co-Authors: Charles Nader, Niclas Björsell, Peter HändelAbstract:In this letter, we discuss the problem of unfolding the frequency spectrum for undersampled wideband data. The problem is of relevance to state-of-the-art radio frequency measurement systems, which capture Repetitive Waveform based on a sampling rate that violates the Nyquist constraint. The problem is presented in a compact form by the inclusion of a complex operator called the CN operator. The ease-of-use problem formulation eliminates the ambiguity caused by folded frequency spectra, in particular those with lines standing on multiples of the Nyquist frequency that are captured with erroneous amplitude and phase values.
Yijiu Zhao - One of the best experts on this subject based on the ideXlab platform.
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A sparse signal reconstruction approach for sequential equivalent time sampling
2016 IEEE International Instrumentation and Measurement Technology Conference Proceedings, 2016Co-Authors: Yijiu Zhao, Xiaoyan ZhuangAbstract:This paper presents a signal reconstruction algorithm for sequential equivalent time sampling (SETS). SETS has been incorporated in digital acquisition system to capture a Repetitive Waveform with a single analog to digital converter (ADC) clocked at a rate that is much lower than the signal's Nyquist rate. However, in order to achieve a high time resolution, a great number of acquisition runs need to be carried out. In this paper, the sparsity of underlying signal is exploited, and compressed sensing (CS) theory is employed to reconstruct signal from sub-Nyquist samples captured by SETS system. The CS measurement matrix is constructed in the context of SETS. Experimental results indicate that, the proposed CS-based reconstruction is feasible, and the sparse signal could be reconstructed from a small number of SETS samples. Compared to the traditional SETS signal reconstruction, the number used to signal reconstruction could be significantly reduced.
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Minimum Rate Sampling and Spectrum Blind Reconstruction in Random Equivalent Sampling
Circuits Systems and Signal Processing, 2015Co-Authors: Yijiu Zhao, Li Wang, Houjun Wang, Changjian LiuAbstract:The random equivalent sampling (RES) is a well-known sampling technique that can be used to capture a high-speed Repetitive Waveform with low sampling rate. In this paper, the feasibility of spectrum-blind multiband signal reconstruction for data sampled from RES is investigated. We propose a RES sampling pattern and its corresponding mathematical model that guarantees well-conditioned reconstruction of multiband signal with unknown spectral support. We give the minimum number of RES acquisitions that hold overwhelming probability to successfully reconstruct original signal. We demonstrate that for signal with specific spectral occupation, the number of RES acquisitions and the minimum sampling rate could be approached. The signal reconstruction is studied in the framework of compressive sampling (CS) theory. The eigen-decomposition and minimum description length (MDL) criteria are adopted to adaptively estimate the dimension of signal, and the number of unknowns of reconstruction problem is reduced. Experimental results are reported to indicate that, for a spectrum-blind sparse multiband signal, the proposed reconstruction algorithm for RES is feasible and robust.
Su Liu - One of the best experts on this subject based on the ideXlab platform.
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stereotyped high frequency oscillations discriminate seizure onset zones and critical functional cortex in focal epilepsy
Brain, 2018Co-Authors: Su Liu, Nerses Bebek, Candan Gurses, Altay Sencer, Zhiyi Sha, Michael M Quach, Daniel J Curry, Sujit S Prabhu, Sudhakar Tummala, Thomas R HenryAbstract:High-frequency oscillations in local field potentials recorded with intracranial EEG are putative biomarkers of seizure onset zones in epileptic brain. However, localized 80-500 Hz oscillations can also be recorded from normal and non-epileptic cerebral structures. When defined only by rate or frequency, physiological high-frequency oscillations are indistinguishable from pathological ones, which limit their application in epilepsy presurgical planning. We hypothesized that pathological high-frequency oscillations occur in a Repetitive fashion with a similar Waveform morphology that specifically indicates seizure onset zones. We investigated the Waveform patterns of automatically detected high-frequency oscillations in 13 epilepsy patients and five control subjects, with an average of 73 subdural and intracerebral electrodes recorded per patient. The Repetitive oscillatory Waveforms were identified by using a pipeline of unsupervised machine learning techniques and were then correlated with independently clinician-defined seizure onset zones. Consistently in all patients, the stereotypical high-frequency oscillations with the highest degree of Waveform similarity were localized within the seizure onset zones only, whereas the channels generating high-frequency oscillations embedded in random Waveforms were found in the functional regions independent from the epileptogenic locations. The Repetitive Waveform pattern was more evident in fast ripples compared to ripples, suggesting a potential association between Waveform repetition and the underlying pathological network. Our findings provided a new tool for the interpretation of pathological high-frequency oscillations that can be efficiently applied to distinguish seizure onset zones from functionally important sites, which is a critical step towards the translation of these signature events into valid clinical biomarkers.awx374media15721572971001.