Hilbert-Huang versus Morlet wavelet transformation on mismatch negativity of children in uninterrupted sound paradigm

Background. Compared to the waveform or spectrum analysis of event-related potentials (ERPs), time-frequency representation (TFR) has the advantage of revealing the ERPs time and frequency domain information simultaneously. As the human brain could be modeled as a complicated nonlinear system, it is interesting from the view of psychological knowledge to study the performance of the nonlinear and linear time-frequency representation methods for ERP research. In this study Hilbert-Huang transformation (HHT) and Morlet wavelet transformation (MWT) were performed on mismatch negativity (MMN) of children. Participants were 102 children aged 8–16 years. MMN was elicited in a passive oddball paradigm with duration deviants. The stimuli consisted of an uninterrupted sound including two alternating 100 ms tones (600 and 800 Hz) with infrequent 50 ms or 30 ms 600 Hz deviant tones. In theory larger deviant should elicit larger MMN. This theoretical expectation is used as a criterion to test two TFR methods in this study. For statistical analysis MMN support to absence ratio (SAR) could be utilized to qualify TFR of MMN. Results. Compared to MWT, the TFR of MMN with HHT was much sharper, sparser, and clearer. Statistically, SAR showed significant difference between the MMNs elicited by two deviants with HHT but not with MWT, and the larger deviant elicited MMN with larger SAR. Conclusion. Support to absence ratio of Hilbert-Huang Transformation on mismatch negativity meets the theoretical expectations, i.e., the more deviant stimulus elicits larger MMN. However, Morlet wavelet transformation does not reveal that. Thus, HHT seems more appropriate in analyzing event-related potentials in the time-frequency domain. HHT appears to evaluate ERPs more accurately and provide theoretically valid information of the brain responses.peerReviewe

The influence of dataset size on the performance of cell outage detection approach in LTE-A networks

The configuration and maintenance of constantly evolving mobile cellular networks are getting more and more complex and hence expensive. Self-Organizing Networks (SON) concept is an umbrella term for the set of automated solutions for network operations proposed by 3rd Generation Partnership Project (3GPP) group. Automated cell outage detection is one of the components of SON functionality. In early studies our research group developed data-driven approach for the detection of malfunctioning cells. In this paper we investigate the performance of the proposed solution as a function of the density of active users and the size of observation interval. The evaluation is conducted in Long Term Evolution (LTE)/LTE-Advanced (LTE-A) system level simulator. The analyzed data is the collection of Minimization of Drive Testing (MDT) reports, which is basically user-level statistics. Our approach is able to detect cells experiencing random access failures, but the performance depends on the amount of available data

Jammer Suppression in DS-CDMA Arrays Using Independent Component Analysis

(ICA) as an advanced pre-processing tool for blind suppression of interfering jammer signals in direct sequence spread spectrum communication systems utilizing antenna arrays. The role of ICA is to provide a jammer-mitigated signal to the conventional detection. If the jammer signal is weak or absent, preprocessing by ICA is not advisable. Therefore we also consider two possible switching schemes, called pre-switching and post-switching, which activate the ICA-based jammer canceller only when it is expected to improve conventional detection. ICA-RAKE preswitching is less complex, while post-switching performs better, especially when the jammer is pulsed in nature. Simulations are given to illustrate the achieved performance gains for single- and multi-path channels. Index Terms— I

Jammer Cancellation In

In this paper Independent Component Analysis (ICA) is considered for blind interference cancellation in a direct sequence spread spectrum communication system utilizing antenna arrays. Recently, an ICA-assisted interference canceler was proposed [1]. This receiver structure is an extension to the framework proposed in [2], in which blind source separation (BSS) techniques were utilized to the jammer mitigation problem. A common feature for both is that they apply an advanced pre-processing tool to o#er an unjammed signal for conventional detection. However, it is not always desirable to apply the pre-processing tool, since it might even cause additional interference if the jammer is weak or absent. What would make the receivers more practical is to switch the additional canceler active only whenever it is expected to improve conventional detection. In this paper we compare two possible switching strategies at both ends of the receiver chain, pre and post switching schemes, and evaluate their impacts to the overall performance improvement of the array receiver

The reliability of continuous brain responses during naturalistic listening to music

Low-level (timbral) and high-level (tonal and rhythmical) musical features during continuous listening to music, studied by functional magnetic resonance imaging (fMRI), have been shown to elicit large-scale responses in cognitive, motor, and limbic brain networks. Using a similar methodological approach and a similar group of participants, we aimed to study the replicability of previous findings. Participants' fMRI responses during continuous listening of a tango Nuevo piece were correlated voxelwise against the time series of a set of perceptually validated musical features computationally extracted from the music. The replicability of previous results and the present study was assessed by two approaches: (a) correlating the respective activation maps, and (b) computing the overlap of active voxels between datasets at variable levels of ranked significance. Activity elicited by timbral features was better replicable than activity elicited by tonal and rhythmical ones. These results indicate more reliable processing mechanisms for low-level musical features as compared to more high-level features. The processing of such high-level features is probably more sensitive to the state and traits of the listeners, as well as of their background in music