The course objective is to provide to students suitable lectures about scientific computing and procedures for electric and electronics applications, in order to understand and to design simulation software.
teacher profile teaching materials
- introduction to the programming environment (Matlab)
- computer representation of real numbers
- considerations of numerical patterns and errors
- calculation of the zeros of a function
- approximation of functions and data
- numerical derivation
- numerical integration
- numerical resolution of ordinary differential equations
---- part two:
- algorithms and optimization models
- introduction to systems
- linear and nonlinear systems
- mathematical optimization models
- optimization algorithms
- introduction to machine learning
- theory and programming of artificial neural network training algorithms
- theory and programming of fully-connected artificial neural networks
- theory and programming of convolutional neural networks (CNN)
- theory and programming of generative neural networks (GAN)
- theory and programming of recurrent neural networks (RNNs)
- example of applications of machine learning to engineering
Lecturer's handouts
Programme
Part one: computational tools- introduction to the programming environment (Matlab)
- computer representation of real numbers
- considerations of numerical patterns and errors
- calculation of the zeros of a function
- approximation of functions and data
- numerical derivation
- numerical integration
- numerical resolution of ordinary differential equations
---- part two:
- algorithms and optimization models
- introduction to systems
- linear and nonlinear systems
- mathematical optimization models
- optimization algorithms
- introduction to machine learning
- theory and programming of artificial neural network training algorithms
- theory and programming of fully-connected artificial neural networks
- theory and programming of convolutional neural networks (CNN)
- theory and programming of generative neural networks (GAN)
- theory and programming of recurrent neural networks (RNNs)
- example of applications of machine learning to engineering
Core Documentation
QUARTERONI ALFIO; SALERI FAUSTO - CALCOLO SCIENTIFICO. ESERCIZI E PROBLEMI RISOLTI CON MATLAB E OCTAVE - ED. SPRINGER VERLAGLecturer's handouts
Reference Bibliography
---Type of delivery of the course
Frontal lessons Computer simulationsType of evaluation
Presentation of a research on themes parallel to those covered in the course. Oral examination