Kernel methods provide an efficient mechanism to derive nonlinear algorithms. In classification problems as well as in feature extraction, kernel-based approaches map the original...
Abstract— This paper proposes a maximum likelihood detection (MLD) method for the differential space-time block code (DSTBC) in cooperation with blind linear prediction (BLP) of ...
Time-series segmentation in the fully unsupervised scenario in which the number of segment-types is a priori unknown is a fundamental problem in many applications. We propose a Ba...
The main computational cost in Fractal Image Analysis (FIC) comes from the required range-domain full block comparisons. In this work we propose a new algorithm for this comparison...
— this paper presents a novel image feature extraction and recognition method two dimensional linear discriminant analysis (2DLDA) in a much smaller subspace. Image representatio...
R. M. Mutelo, Li Chin Khor, Wai Lok Woo, Satnam Si...