However, this is in general only an approximation aimed at simplifying the problem and this leads to inaccuracies that are detrimental to the application, and it is therefore preferable to consider the multichannel case when possible.
Center point approximation aims to extract the center point of each individual particle in the image, thus resulting in a set of estimated coordinates of all particles present in the image.
Our approach is a combination of interval arithmetic (over-approximation, aiming to decide unsatisfiability) and testing (under-approximation, aiming to decide satisfiability) to sandwich precise results.
Previous works, e.g.[8, 14, 15], propose approximations aimed at reducing the communication cost, but, in all aforementioned schemes, processing and sensing at different time scales are still required.
Eq. (25) will be subject to a set of approximations aiming to derive the scaled Wigner Boltzmann equation.
Based on this new formulation of the CCA problem, we developed a new sparse CCA based on penalized rank-1 matrix approximation which aims to overcome the drawback of CCA in the context of high-dimensional data and improved interpretability.
Non-linear regression methods such as the well-known Levenberg Marquardt algorithm involve successive approximations that aim at minimizing an error function (Marquardt, 1963).
A brief discussion of some analytical approaches in the literature is presented and calculations using the second-order vector potential approximation are introduced, aimed at the study of the influence of coil shape and size on the sensitivity to electrical conductivity of the substrate.
Future work will thus focus on controlled approximations with the aim of a drastic reduction of both: CPU and memory consumption.
In order to get a better sense of the impact of different approximations, this work aims to compare results obtained based on different approximate methodologies with an exact method, namely the NUDUNA Monte Carlo based approach developed by AREVA GmbH.
We discuss a number of ecologically important quantities that can be derived from the full stochastic models and their deterministic approximations, with a particular aim of characterizing the respective roles of the structure of the landscape and the properties of the species.
