Guided Discrimination and Correlation Subspace Learning for Domain Adaptation.

As a branch of transfer learning, domain adaptation leverages useful knowledge from a source domain to a target domain for solving target tasks. Most of the existing domain adaptation methods focus on how to diminish the conditional distribution shift and learn invariant features between different domains. However, two important factors are overlooked by most existing methods: 1) the transferred features should be not only domain invariant but also discriminative and correlated, and 2) negative transfer should be avoided as much as possible for the target tasks.

Canonical Correlation Analysis With Low-Rank Learning for Image Representation.

As a multivariate data analysis tool, canonical correlation analysis (CCA) has been widely used in computer vision and pattern recognition. However, CCA uses Euclidean distance as a metric, which is sensitive to noise or outliers in the data. Furthermore, CCA demands that the two training sets must have the same number of training samples, which limits the performance of CCA-based methods.

Spectrum Sharing Based on a Bertrand Game in Cognitive Radio Sensor Networks.

In the study of power control and allocation based on pricing, the utility of secondary users is usually studied from the perspective of the signal to noise ratio. The study of secondary user utility from the perspective of communication demand can not only promote the secondary users to meet the maximum communication needs, but also to maximize the utilization of spectrum resources, however, research in this area is lacking, so from the viewpoint of meeting the demand of network communication, this paper designs a two stage model to solve spectrum leasing and allocation problem in cognitive radio sensor networks (CRSNs). In the first stage, the secondary base station collects the secondary network communication requirements, and rents spectrum resources from several primary base stations using the Bertrand game to model the transaction behavior of the primary base station and secondary base station.

An Effective On-line Polymer Characterization Technique by Using SALS Image Processing Software and Wavelet Analysis.

This paper describes an effective on-line polymer characterization technique by using small-angle light-scattering (SALS) image processing software and wavelet analysis. The phenomenon of small-angle light scattering has been applied to give information about transparent structures on morphology. Real-time visualization of various scattered light image and light intensity matrices is performed by the optical image real-time processing software for SALS.