CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2019/2020

# Simulation of Biological Systems

Code Completion Credits Range Language
E374013 Z,ZK 5 2P+2C
Lecturer:
Vladimír Hlaváč (guarantor)
Tutor:
Vladimír Hlaváč (guarantor)
Supervisor:
Department of Instrumentation and Control Engineering
Synopsis:

Modelling of biological dynamic systems, from single unit to population. Biological and artificial neuron, catastrophe theory, compartment models. Basic numerical description of dynamic systems and its solution in Matlab.

Subject web pages: http://iat.fs.cvut.cz/sbs

Requirements:

Attending students should have accomplished basic course of mathematics on differential equations.

Syllabus of lectures:

Artificial/biological neuron

biological neuron description

artificial neuron network, perceptron, MLP, back propagation

other types (radial based, Hopfield network, model of memory)

homeostatic neural network

Artificial live

The „live game“ simulation

Cellular automata

Swarm intelligence

Artificial ants (vant-s)

Population simulation - single population, dual (hare-wolf), three population (+vegetation grow)

Modeling of process

differential equation for dynamic description

compartment method

deterministic chaos, Lorentz attractor

catastrophic theory, examples of use

Identification

using known model, guessing parameters (gradient descent)

using feed forward neural network

using swarm/genetic algorithm

data analysis (correlation, autocorrelation, Fourier transform)

Syllabus of tutorials:

1-2 Useful programming techniques, worksheet calculators, introduction to Matlab,Maple, Simulink, efficency of matrix and vector operations in Matlab.

3-4 Fundamentals on modelling dynamical systems, linear s

3-4 Simulation of simple catastrophic models. Simulation of bifurcations in models of beetle population. Simulation of continuous chaotic model (MS Excel, demonstration of program Maple).

5-6Determining parameters for state space reconstruction (False Neighbors Method, Mutual Information). Automated design of an artificial neural network model predicting heart-beat rhythm; designing a model from measured data (R-R recordings) (MS Excel, Dataplore, Matlab/Simulink).

7-8Simulation of monitoring the actual changes in the dynamics of cardiovascular system with higher-order nonlinear neural units (HONNU) (Matlab/Simulink)

9-10Automated design of adaptive neuro-fuzzy model of combined anesthetics effects with uncertainty in measured data (MS Excel, Matlab/Simulink ANFIS).

11-12The model of the fast control influences of autonomous neural system affecting the heart-rate variability (Matlab/Simulink).

13-14Accomplishing projects, consulting, credits

Study Objective:

Students will practice modeling techniques related to the deterministic chaos, quasiperiodic behavior, synchronization, uncertainty, neural networks, model optimization, adaptation, and will become familiar with related terms.

Study materials:

Subject web page: http://iat.fs.cvut.cz/sbs/

Note:
Time-table for winter semester 2019/2020:
Time-table is not available yet
Time-table for summer semester 2019/2020:
Time-table is not available yet
The course is a part of the following study plans:
Data valid to 2020-01-19
For updated information see http://bilakniha.cvut.cz/en/predmet2114906.html