Abstract Graph collaborative filtering methods have shown great performance improvements compared with deep neural network-based models. However, these suffer from data sparsity and noise problems. To address issues, we propose a new contrastive learning-based graph method to learn more robust representations. The proposed is called signal enhanced (SC-GCF), which conducts learning on signals. ...

As a particular kind of detection technology under weak magnetization, metal magnetic memory testing is very likely to be affected by external factors in the detecting process, which may lead incorrect results. In order minimize negative influence interrupting signals and improve accuracy, this paper adopted enhanced method preliminarily increase signal-to-noise ratio (SNR) signal then compares...

This paper presents a signal analysis technique for machine health monitoring based on the Hilbert-Huang Transform (HHT). The HHT represents a time-dependent series in a two-dimensional (2-D) time-frequency domain by extracting instantaneous frequency components within the signal through an Empirical Mode Decomposition (EMD) process. The analytical background of the HHT is introduced, based on ...

the purpose of this study was to examine how four teachers used the seven processes of videotape analysis to develop an analytic approach and reflective thinking towards their teaching. the study was organized within video clubs and was used to describe the interactions among four teachers about their experiences at a language institute. data were gathered through videotaped recordings of lesso...

This paper describes a system architecture along with signal processing technique which allows a reduction in the complexity of a 3.1–10.6 GHz Ultra-Wideband radio. The proposed system transmits passband pulses using a pulser and antenna, and the receiver front-end down-converts the signal frequency by subsampling, thus, requiring substantially less hardware than a traditional narrowband approa...