Accelerating the numerical solution of thermal runaway in Li-ion batteries
Computational modeling and simulation of thermal runaway in Li-ion batteries is an effective
tool to understand safety concerns associated with Li-ion batteries. However, thermal …
tool to understand safety concerns associated with Li-ion batteries. However, thermal …
Intrinsic noise improves speech recognition in a computational model of the auditory pathway
Noise is generally considered to harm information processing performance. However, in the
context of stochastic resonance, noise has been shown to improve signal detection of weak …
context of stochastic resonance, noise has been shown to improve signal detection of weak …
Stochastic Motion Planning as Gaussian Variational Inference: Theory and Algorithms
We consider the motion planning problem under uncertainty and address it using
probabilistic inference. A collision-free motion plan with linear stochastic dynamics is …
probabilistic inference. A collision-free motion plan with linear stochastic dynamics is …
Building a realistic virtual simulator for unmanned aerial vehicle teleoperation
ME Mora-Soto, J Maldonado-Romo… - Applied Sciences, 2021 - mdpi.com
Unmanned Aerial Vehicles (UAVs) support humans in performing an increasingly varied
number of tasks. UAVs need to be remotely operated by a human pilot in many cases …
number of tasks. UAVs need to be remotely operated by a human pilot in many cases …
Doubly fed induction wind generators model and field orientation vector control design and implementation on FPGA
Dynamic systems emulators are very efficient techniques to design a system that mimics a
precise behaviour of real systems. Moreover, they are designed to reduce costs as well as to …
precise behaviour of real systems. Moreover, they are designed to reduce costs as well as to …
An efficient ODE-solving method based on heuristic and statistical computations: αII-(2+ 3) P method
M Babaei - The Journal of Supercomputing, 2024 - Springer
The main goal of this paper is to develop a new class of sixth-and fourth-order implicit
Runge–Kutta methods to treat linear and nonlinear initial value ordinary differential …
Runge–Kutta methods to treat linear and nonlinear initial value ordinary differential …
UltraSynth: insights of a CGRA integration into a control engineering environment
D Wolf, A Engel, T Ruschke, A Koch… - Journal of Signal …, 2021 - Springer
Abstract Coarse Grained Reconfigurable Arrays (CGRAs) or Architectures are a concept for
hardware accelerators based on the idea of distributing workload over Processing Elements …
hardware accelerators based on the idea of distributing workload over Processing Elements …
Contribution to Speeding-Up the Solving of Nonlinear Ordinary Differential Equations on Parallel/Multi-Core Platforms for Sensing Systems
V Tavakkoli, K Mohsenzadegan, JC Chedjou… - Sensors, 2020 - mdpi.com
Solving ordinary differential equations (ODE) on heterogenous or multi-core/parallel
embedded systems does significantly increase the operational capacity of many sensing …
embedded systems does significantly increase the operational capacity of many sensing …
Application of difference schemes to decision the pursuit problem
VF Ochkov, IE Vasileva - Информатика и автоматизация, 2019 - ia.spcras.ru
The problem of the pursuit curve construction in the case when the tangent to pursuer's
motion trajectory passes at any time through the point representing the pursued is …
motion trajectory passes at any time through the point representing the pursued is …
Ultrasynth: integration of a CGRA into a control engineering environment
D Wolf, T Ruschke, C Hochberger, A Engel… - … Symposium, ARC 2019 …, 2019 - Springer
Abstract Coarse Grained Reconfigurable Arrays (CGRAs) can exploit parallelism of compute-
intense applications by distributing their workload across a set of Processing Elements …
intense applications by distributing their workload across a set of Processing Elements …