When a flow is not allowed to be reoriented the Maximum Residual Flow Problem with k-Arc Destruction is known to be NP -hard for k = 2. We show that when a flow is allowed to be adaptive the problem becomes polynomial for every fixed k.

We present and rigorously analyze a generalization of the WinnerTake-All Network: the K-Winners-Take-All Network. This network identifies the K largest of a set of N real numbers. The network model used is the continuous Hopfield model.

Siamese networks have achieved great success in visual tracking with the advantages of speed and accuracy. However, how to track an object precisely robustly still remains challenging. One reason is that multiple types features are required achieve good precision robustness, which unattainable by a single training phase. Moreover, usually struggle online adaption problem. In this paper, we pres...

We present a Hamilton cycle in the k-sided pancake network and four combinatorial algorithms to traverse cycle. The network’s vertices are coloured permutations $$\pi = p_1p_2\cdots p_n$$ , where each $$p_i$$ has an associated colour $$\{0,1,\ldots k\,-\,1\}$$ . There is directed edge $$(\pi _1,\pi _2)$$ if _2$$ can be obtained from _1$$ by “flip” of length j, which reverses first j elements in...