activity
20182022
most citedPhysical Modeling using Recurrent Neural Networks with Fast Convolutional Layers

6 citations · 6 across the 2 of their papers we have counts for

collaborators

5 papers

cs.SD2022★ 6 cited

Physical Modeling using Recurrent Neural Networks with Fast Convolutional Layers

Julian D. Parker, Sebastian J. Schlecht, Rudolf Rabenstein +1

Discrete-time modeling of acoustic, mechanical and electrical systems is a prominent topic in the musical signal processing literature. Such models are mostly derived by discretizi…

cs.ET2021

Channel Responses for the Molecule Release from Spherical Homogeneous Matrix Carriers

Maximilian Schäfer, Yolanda Salinas, Alexander Ruderer +6

Molecular communications is a promising framework for the design of controlled-release drug delivery systems. Under this framework, drug carriers, diseased cells, and the channel a…

cs.ET2020

Transfer Function Models for Cylindrical MC Channels with Diffusion and Laminar Flow

Maximilian Schäfer, Wayan Wicke, Lukas Brand +2

The analysis and design of advection-diffusion based molecular communication (MC) systems in cylindrical environments is of particular interest for applications such as micro-fluid…

cs.ET2019

Spherical Diffusion Model with Semi-Permeable Boundary: A Transfer Function Approach

Maximilian Schäfer, Wayan Wicke, Werner Haselmayr +2

The derivation of suitable analytical models is an important step for the design and analysis of molecular communication systems. However, many existing models have limited applica…

physics.comp-ph2018

Analytical Models for Particle Diffusion and Flow in a Horizontal Cylinder with a Vertical Force

Maximilian Schäfer, Wayan Wicke, Rudolf Rabenstein +1

This paper considers particle propagation in a cylindrical molecular communication channel, e.g. a simplified model of a blood vessel. Emitted particles are influenced by diffusion…