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Microsimulation of urban systems evolution requires synthetic population as a key input. Currently, the focus is on treating synthesis as a fitting problem and thus various techniques have been developed, including Iterative Proportional Fitting (IPF) and ...
We introduce a new family of explicit integrators for stiff Ito stochastic differential equations (SDEs) of weak order two. These numerical methods belong to the class of one-step stabilized methods with extended stability domains and do not suffer from th ...
Machine learning algorithms are widely used today for analytical tasks such as data cleaning, data categorization, or data filtering. At the same time, the rise of social media motivates recent uptake in large scale graph processing. Both categories of alg ...
A novel method for quantitative lateral force measurement (LFM) calibration has been developed. Using a single-molecule spectroscopy approach it is possible to calibrate the AFM levers for both lateral and normal spring constants with a single image scan. ...
We describe a mass spectra recalibration method, which enables analysis of petroleum samples with Orbitrap FTMS. In this method, the mass calibration function is estimated on the basis of mass-to-charge ratios and abundances of internal calibrants without ...
In this work, we study the mean-square-error performance of a diffusion strategy for continuous-time estimation over networks. We derive differential equations that describe the evolution of the mean and correlation of the weight-error vector, and provide ...
In this work, we consider a distributed beam coordination problem, where a collection of arrays are interconnected by a certain topology. The beamformers employ an adaptive diffusion strategy to compute the beamforming weight vectors by relying solely on c ...
Adaptive networks rely on in-network and collaborative processing among distributed agents to deliver enhanced performance in estimation and inference tasks. Information is exchanged among the nodes, usually over noisy links. This paper first investigates ...
We derive an adaptive diffusion mechanism to optimize global cost functions in a distributed manner over a network of nodes. The cost function is assumed to consist of the sum of individual components, and diffusion adaptation is used to enable the nodes t ...
Adaptive networks rely on in-network and collaborative processing among distributed agents to deliver enhanced performance in estimation and inference tasks. Information is exchanged among the nodes, usually over noisy links. The combination weights that a ...