We introduce a complexity measure of modal properties of finite structures which generalises the automaticity of languages. It is based on graph-automata like devices called labelling systems. We define a measure of the size of a structure that we call rank, and show that any modal property of structures can be approximated up to any fixed rank n by a labelling system. The function that takes n...

We propose a new language, RLucid, which is Lucid with one new operator. RLucid is intended for real time (or, more precisely, reactive) programming and is based on a simple synchronous dataflow model of computation. RLucid is therefore similar to the Lustre language but is more general in that it does not require that operators be strict: in the RLucid model a filter may respond when input arr...

This paper investigates a wireless powered communication network (WPCN) under the protocol of harvest-thentransmit, where a hybrid access point with constant power supply replenishes the passive user nodes by wireless power transfer in the downlink, then each user node transmit independent information to the hybrid AP in a time division multiple access (TDMA) scheme in the uplink. The sum-throu...

We consider the off-policy evaluation problem in Markov decision processes with function approximation. We propose a generalization of the recently introduced emphatic temporal differences (ETD) algorithm (Sutton, Mahmood, and White, 2015), which encompasses the original ETD(λ), as well as several other off-policy evaluation algorithms as special cases. We call this framework ETD(λ, β), where o...

The immersed boundary (IB) method is an algorithm for simulating elastic structures immersed in a fluid. The IB method can be used, for example, to simulate blood flow in the heart. Even running on supercomputers, software implementations require on the order of seven CPU-days to simulate one heart beat. The IB method has significant, inherent, fine-grain parallelism available. This parallelism...

We consider online learning of Bayesian network classifiers (BNCs) with reduced-precision parameters, i.e. the conditional-probability tables parameterizing the BNCs are represented by low bit-width fixedpoint numbers. In contrast to previous work, we analyze the learning of these parameters using reduced-precision arithmetic only which is important for computationally constrained platforms, e....

In this paper we study the comprehensive effects on volume rendered images due to numerical errors caused by the use of finite precision for data representation and processing. To estimate actual error behavior we conduct a thorough study using a volume renderer implemented with arbitrary floating-point precision. Based on the experimental data we then model the impact of floating-point pipelin...

Two graphs are co-spectral if their respective adjacency matrices have the same multi-set of eigenvalues. A graph is said to be determined by its spectrum if all graphs that are co-spectral with it are isomorphic to it. We consider these properties in relation to logical definability. We show that any pair of graphs that are elementarily equivalent with respect to the three-variable counting fi...

Entanglement is a complexity measure of digraphs that origins in fixedpoint logics. Its combinatorial purpose is to measure the nested depth of cycles in digraphs. We address the problem of characterizing the structure of graphs of entanglement at most k. Only partial results are known so far: digraphs for k = 1, and undirected graphs for k = 2. In this paper we investigate the structure of und...

Despite the considerable research effort towards the analysis and understanding of the nature of turbo decoding, a clear identification of the underlying optimization problem the turbo decoder attempts to solve is still missing. In this paper, we link the turbo decoding algorithm to maximum likelihood (ML) sequence detection by demonstrating how the turbo decoder can be systematically derived s...