Abstract Typically, monitoring quality characteristics of very personalized products is a difficult task due to the lack experimental data. This typical case processes where production volume continues shrink growing complexity and customization products, thus requiring low-volume productions. paper presents novel approach statistically monitor defects-per-unit (DPU) assembled based on use defe...

The generation of pleasant prosody parameters is very important for speech synthesis. A prosody generation unit can be seen as a dynamical system. In this paper sophisticated time-delay recurrent neural network (NN) topologies are presented which can be used for the modeling of dynamical systems. Within the prosody prediction task left and right context information is known to influence the pre...

In this paper, we propose a parallel intra-operation unit and a memory architecture for improving the performance of intraprediction, which utilizes spatial correlation in an image to predict the blocks and contains 17 prediction modes in total. The design is targeted for portable devices applying H.264/AVC decoders. For boosting the performance of the proposed design, we adopt a parallel intra...

Over the past few years, there has been increased interest in data mining and machine learning methods to improve hospital performance. Research has focused on prediction of measurable outcomes, including mortality, risk of complications and length of hospital stay. Length of stay is an important metric both for healthcare providers and patients, and is influenced by numerous factors. In partic...

A method to characterize dynamical interdependence among nonlinear systems is derived based on mutual nonlinear prediction. Systems with nonlinear correlation will show mutual nonlinear prediction when standard analysis with linear cross correlation might fail. Mutual nonlinear prediction also provides information on the directionality of the coupling between systems. Furthermore, the existence...

The generation of pleasant prosody parameters is very important for speech synthesis. A Prosody generation unit can be seen as a dynamical system. In this paper sophisticated time-delay recurrent neural network (NN) topologies are presented which can be used for the modeling of dynamical systems. Within the prosody prediction task left and right context information is known to influence the pre...

The predictive learning of spatiotemporal sequences aims to generate future images by learning from the historical frames, where spatial appearances and temporal variations are two crucial structures. This paper models these structures by presenting a predictive recurrent neural network (PredRNN). This architecture is enlightened by the idea that spatiotemporal predictive learning should memori...