This paper considers the convergence problem in autonomous mobile robot systems. A natural algorithm for the problem requires the robots to move towards their center of gravity. Th...
—Oja’s principal subspace algorithm is a well-known and powerful technique for learning and tracking principal information in time series. A thorough investigation of the conve...
We propose a new low complexity and fast converging frequencydomain adaptive algorithm for sparse system identification. This is achieved by exploiting the MMax and SP tap-select...
Andy W. H. Khong, Xiang Lin, Milos Doroslovacki, P...
Abstract. In this paper, a general framework of quantum-inspired multiobjective evolutionary algorithms is proposed based on the basic principles of quantum computing and general s...
In Reinforcement Learning (RL) there has been some experimental evidence that the residual gradient algorithm converges slower than the TD(0) algorithm. In this paper, we use the ...