Keyword Spotting (KWS) is an essential component in a smart device for alerting the system when user prompts it with command. As these devices are typically constrained by computational and energy resources, KWS model should be designed small footprint. In our previous work, we developed lightweight dynamic filters which extract robust feature map within noisy environment. The learning variable...

We present a framework for the estimation of transfer entropy (TE) under the conditions typical of physiological system analysis, featuring short multivariate time series and the presence of instantaneous causality (IC). The framework is based on recognizing that TE can be interpreted as the difference between two conditional entropy (CE) terms, and builds on an efficient CE estimator that comp...

BACKGROUND Although measurement of cerebral hypnotic drug effect and muscle relaxation is common clinical routine during anaesthesia, a reliable measurement of the neurophysiological effects evoked by a painful stimulus is still missing. Recently, the surgical stress index (SSI) has been introduced as a surrogate measure of 'nociception'. The present study aimed to examine the influence of incr...

We study the impact of different loss functions on lesion segmentation from medical images. Although Cross-Entropy (CE) is most popular option when dealing with natural images, for biomedical image soft Dice often preferred due to its ability handle imbalanced scenarios. On other hand, combination both has also been successfully applied in these types tasks. A much less studied problem generali...

Multisensor image fusion is a process of combining information from multiple sensors. A newly noninvasive neurosurgical method that requires image fusion is the Gamma Knife. In this paper we present and evaluate advanced image fusion algorithms for Matlab platform and DICOM images helping efficiently the innovative Gamma Knife treatment planning. This method is first time ever introduced in cli...

One consequence of situated face-to-face conversation is the coobservability of participants’ respiratory movements and sounds. We explore whether this information can be exploited in predicting incipient speech activity. Using a methodology called stochastic turn-taking modeling, we compare the performance of a model trained on speech activity alone to one additionally trained on static and dy...

Mixability of a loss characterizes fast rates in the online learning setting of prediction with expert advice. The determination of the mixability constant for binary losses is straightforward but opaque. In the binary case we make this transparent and simpler by characterising mixability in terms of the second derivative of the Bayes risk of proper losses. We then extend this result to multicl...

Article history: Received 19 October 2011 Received in revised form 8 March 2013 Accepted 4 July 2013 Available online xxxx

OBJECTIVE A defining feature of physiological systems under the neuroautonomic regulation is their dynamical complexity. The most common approach to assess physiological complexity from short-term recordings, i.e. to compute the rate of entropy generation of an individual system by means of measures of conditional entropy (CE), does not consider that complexity may change when the investigated ...

In this paper, a method is presented for the efficient estimation of rare-event (buffer overflow) probabilities in queueing networks using importance sampling. Unlike previously proposed change of measures, the one used here is not static, i.e., it depends on the buffer contents at each of the network nodes. The ‘optimal’ state-dependent change of measure is determined adaptively during the sim...