PCA and K-means clustering applied to Raman and PL imaging reveal structural defects in silicon wafers, enhancing understanding of optoelectronic performance.

Unlike PCA (maximum variance) or ICA (maximum independence), ForeCA finds components that are maximally forecastable. This makes it ideal for time series analysis where prediction is often the primary ...

AI tools are frequently used in data visualization — this article describes how they can make data preparation more efficient ...

Abstract: Global navigation satellite system (GNSS) spoofing attacks pose a serious threat to existing 5G and future 6G networks, as they rely heavily on the high-precision time synchronization ...

Abstract: Tensor robust principal component analysis (TRPCA), as a popular linear low-rank method, has been widely applied to various visual tasks. The mathematical process of the low-rank prior is ...