Improved message passing for inference in densely connected systems

An improved inference method for densely connected systems is presented. The approach is based on passing condensed messages between variables, representing macroscopic averages of microscopic messages. We extend previous work that showed promising results in cases where the solution space is contiguous to cases where fragmentation occurs. We apply the method to the signal detection problem of Code Division Multiple Access (CDMA) for demonstrating its potential. A highly efficient practical algorithm is also derived on the basis of insight gained from the analysis. © EDP Sciences.

Message passing for task redistribution on sparse graphs

The problem of resource allocation in sparse graphs with real variables is studied using methods of statistical physics. An efficient distributed algorithm is devised on the basis of insight gained from the analysis and is examined using numerical simulations, showing excellent performance and full agreement with the theoretical results.

Formation of droplets from the liquid wall film passing through the inlet port of a spark ignition engine

The available literature has been surveyed to determine the parameters affecting fuelling requirements of spark ignition engines and their relation to engine performance and emissions. Theories and experiment relating to two phase and multi-component flows have also been examined and the techniques employed in the measurement of droplet sizes and liquid wall films have been reviewed. Following preliminary steady flow visualisation experiments to examine the trajectories of droplets discharging from the valve port an extensive practical investigation of the spectrum of droplet sizes formed by the break up of the wall film has produced results which have been correlated in terms of the important fuel and airflow parameters. It is concluded that the Sauter mean diameter of droplets formed by the break up of the wall film will vary between 70 and 150 m, depending on the operating conditions of the engine. The spectra of droplet sizes measured show that a significant proportion of the total mass of the wall film breaks into drops which will be too large to burn completely and, by comparison with measurements of unburned hydrocarbon emissions from engines supplied with a homogeneous mixture of air and gaseous hydrocarbons, it is concluded that the droplets from the wall film are likely to increase emissions by 50%.

Message-passing algorithms for optimal utilization of cognitive radio networks

Cognitive Radio has been proposed as a key technology to significantly improve spectrum usage in wireless networks by enabling unlicensed users to access unused resource. We present new algorithms that are needed for the implementation of opportunistic scheduling policies that maximize the throughput utilization of resources by secondary users, under maximum interference constraints imposed by existing primary users. Our approach is based on the Belief Propagation (BP) algorithm, which is advantageous due to its simplicity and potential for distributed implementation. We examine convergence properties and evaluate the performance of the proposed BP algorithms via simulations and demonstrate that the results compare favorably with a benchmark greedy strategy. © 2013 IEEE.

Message-passing for inference and optimization of real variables on sparse graphs

The inference and optimization in sparse graphs with real variables is studied using methods of statistical mechanics. Efficient distributed algorithms for the resource allocation problem are devised. Numerical simulations show excellent performance and full agreement with the theoretical results. © Springer-Verlag Berlin Heidelberg 2006.

Message passing for distributed optimisation of power allocation with renewable resources

The increase in renewable energy generators introduced into the electricity grid is putting pressure on its stability and management as predictions of renewable energy sources cannot be accurate or fully controlled. This, with the additional pressure of fluctuations in demand, presents a problem more complex than the current methods of controlling electricity distribution were designed for. A global approximate and distributed optimisation method for power allocation that accommodates uncertainties and volatility is suggested and analysed. It is based on a probabilistic method known as message passing [1], which has deep links to statistical physics methodology. This principled method of optimisation is based on local calculations and inherently accommodates uncertainties; it is of modest computational complexity and provides good approximate solutions.We consider uncertainty and fluctuations drawn from a Gaussian distribution and incorporate them into the message-passing algorithm. We see the effect that increasing uncertainty has on the transmission cost and how the placement of volatile nodes within a grid, such as renewable generators or consumers, effects it.