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Views
Date
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Potential Scenario
817
views
55
downloads
0
comments
2019-Stender_EtAl-Recovery_Of_Differential_Equations_From_Impulse_Response
In this work, a recent method, which allows reconstructing differential equations from time series data, is extended for higher degrees of automation.
time series
regression
response
impulse
oscillation
signal processing
sparse regression
system identification
Free Online Textbook
464
views
95
downloads
0
comments
2012-Brian_Ingalls-Mathematical Modelling in Systems Biology An Introduction
This is a comprehensive text with much biology background to motivate the mathematical modeling, exercises and answers, and many rich examples.
spatial
sensitivity analysis
gene regulatory networks
stochastic
bifurcation
metabolic networks
electrophysiology
transduction
rate laws
biochemical reactions
Potential Scenario
201
views
54
downloads
0
comments
2009-Shamim-EtAl-Investigating viscous damping using a webcam
We describe an experiment involving a mass oscillating in a viscous fluid and analyze overdamped, critically damped and underdamped regimes of harmonic motion.
laboratory
underdamped
overdamped
critically damped
harmonic motion
image processing
viscous fluid
Potential Scenario
123
views
62
downloads
0
comments
1992-Jude_Sommerfeld-More Applied Math Problems on Vessel Draining
From a chemical engineering point of view emptying processing and storage tanks is important and this article considers many issues and shapes of containers. The main interest is in the total time it takes to empty the tank for a collection of...
Torricelli's Law
empty
Torricelli
vessel
container
Potential Scenario
198
views
65
downloads
0
comments
1977-Michael_Mackey-Leon_Glass-Oscillation and Chaos in Physiological Control Systems
First-order nonlinear differential-delay equations describing physiological control systems are studied. The equations display a broad diversity of dynamical behavior including limit cycle oscillation.
sensitivity
chaos
parameters
Respiration
delay
blood cells
Potential Scenario
146
views
92
downloads
0
comments
2017-Alex_Honchar-Neural Networks For Solving Differential Equations
In this post I want to show how I applied simple feed-forward NNs to different differential equations with increasing complexity: ODEs, second order ODEs, and, finally, PDEs.
neural networks
Cybenko theorem
diffusion equation
fluid dynamics
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