Voronoi tessellations specify a partition of a given space according to a set of sites where all points in that space are assigned to the closest site. Capacity-constrained Voronoi tessellations are special cases of Voronoi tessellations in which the region of each site has a predefined area. For example, the capacity constraint could state that each region in a Voronoi tessellation must have t...

Attractor networks have been one of the most successful paradigms in neural computation and have been used as models of computation in the nervous system Many experimentally observed phenomena such as coherent population codes contextual representations and replay of learned neural activity patterns are explained well by attractor dynamics Recently we proposed a paradigm called latent attractor...

   Historically, DNA molecules have been known as the building blocks of life, later on in 1994, Leonard Adelman introduced a technique to utilize DNA molecules for a new kind of computation. According to the massive parallelism, huge storage capacity and the ability of using the DNA molecules inside the living tissue, this type of computation is applied in many application areas such as me...

Cyber-physical system (CPS) provides more powerful service through combining software service and physical device. It is an effective solution to organize various CPS services to realize collaborative decision making (CDM). In CPS, finding out the most competent participators for CDM sponsor is a core problem. To solve this problem, we propose a novel capacity and trust computation based CPS se...

We consider an AWGN channel with a transmitter powered by an energy harvesting source. The node is equipped with a finite energy buffer. Such a system can be modelled as a channel with side information (about energy in the energy buffer) causally known at the transmitter. The receiver may or may not have the side information. We prove that Markov energy management policies are sufficient to ach...

The investigation of information capacity and computation power of threshold elements is motivated by the recent trend of neural-network approaches to pattern recognition. In this correspondence, we estimate lower and upper bounds for the capacity of multilevel threshold elements, using two essentially different enumeration techniques. The results correct a previously published estimate and ind...