In this paper, we develop a spatially-variant (SV) mathematical morphology theory for gray-level signals and images in the euclidean space. The proposed theory preserves the geomet...
—Differential evolution (DE) is arguably one of the most powerful stochastic real-parameter optimization algorithms in current use. DE operates through similar computational step...
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
A complex system is expected to show different nominal behaviors under different conditions, and the deviation over time from these nominal behaviors is an indicator of potential ...
Yanjun Yan, Lisa Ann Osadciw, Glen Benson, Eric Wh...
This paper introduces the software framework MMER Lab which allows an effective assembly of modular signal processing systems optimized for memory efficiency and performance. Our...