The course is aimed at introducing the basic mathematical methods applied in geophysics and their use in Matlab. The main goal is to reach an adequate understanding of such methods and to acquire the capability to develop and use the mathematical tools to study the physical processes of the Earth.
Curriculum
teacher profile teaching materials
Complex numbers and trigonometric functions; phasors.
Introduction to signal analysis; definition of a linear time-invariant system; convolution theorem.
Vector calculus; representation in polar, spherical and curvilinear coordinates.
Wave propagation; standing waves.
Fourier series and transform; Nyquist–Shannon sampling theorem.
Introduction to Python programming and exercise on the topics covered in the theory lessons.
Fruizione: 20410907 ANALISI DEI DATI NELLE GEOSCIENZE in Geologia e Tutela dell'Ambiente LM-74 LAURO SEBASTIAN EMANUEL
Programme
Matrix calculus and linear systems; matrix factorization (eigenvalues, eigenvectors); rigid rototranslations and associated matrix; least squares method and polynomial regression.Complex numbers and trigonometric functions; phasors.
Introduction to signal analysis; definition of a linear time-invariant system; convolution theorem.
Vector calculus; representation in polar, spherical and curvilinear coordinates.
Wave propagation; standing waves.
Fourier series and transform; Nyquist–Shannon sampling theorem.
Introduction to Python programming and exercise on the topics covered in the theory lessons.
Core Documentation
Lecture notes by the teacherType of evaluation
The written test consists in drawing up a report in which the student shows how he has analyzed and discussed some geophysical data, also in relation to what he learned during the lectures. The oral exam focuses on the discussion of the report presented by the student and on the topics covered during the course. teacher profile teaching materials
Complex numbers and trigonometric functions; phasors.
Introduction to signal analysis; definition of a linear time-invariant system; convolution theorem.
Vector calculus; representation in polar, spherical and curvilinear coordinates.
Wave propagation; standing waves.
Fourier series and transform; Nyquist–Shannon sampling theorem.
Introduction to Python programming and exercise on the topics covered in the theory lessons.
Fruizione: 20410907 ANALISI DEI DATI NELLE GEOSCIENZE in Geologia e Tutela dell'Ambiente LM-74 LAURO SEBASTIAN EMANUEL
Programme
Matrix calculus and linear systems; matrix factorization (eigenvalues, eigenvectors); rigid rototranslations and associated matrix; least squares method and polynomial regression.Complex numbers and trigonometric functions; phasors.
Introduction to signal analysis; definition of a linear time-invariant system; convolution theorem.
Vector calculus; representation in polar, spherical and curvilinear coordinates.
Wave propagation; standing waves.
Fourier series and transform; Nyquist–Shannon sampling theorem.
Introduction to Python programming and exercise on the topics covered in the theory lessons.
Core Documentation
Lecture notes by the teacherType of evaluation
The written test consists in drawing up a report in which the student shows how he has analyzed and discussed some geophysical data, also in relation to what he learned during the lectures. The oral exam focuses on the discussion of the report presented by the student and on the topics covered during the course. teacher profile teaching materials
Complex numbers and trigonometric functions; phasors.
Introduction to signal analysis; definition of a linear time-invariant system; convolution theorem.
Vector calculus; representation in polar, spherical and curvilinear coordinates.
Wave propagation; standing waves.
Fourier series and transform; Nyquist–Shannon sampling theorem.
Introduction to Python programming and exercise on the topics covered in the theory lessons.
Fruizione: 20410907 ANALISI DEI DATI NELLE GEOSCIENZE in Geologia e Tutela dell'Ambiente LM-74 LAURO SEBASTIAN EMANUEL
Programme
Matrix calculus and linear systems; matrix factorization (eigenvalues, eigenvectors); rigid rototranslations and associated matrix; least squares method and polynomial regression.Complex numbers and trigonometric functions; phasors.
Introduction to signal analysis; definition of a linear time-invariant system; convolution theorem.
Vector calculus; representation in polar, spherical and curvilinear coordinates.
Wave propagation; standing waves.
Fourier series and transform; Nyquist–Shannon sampling theorem.
Introduction to Python programming and exercise on the topics covered in the theory lessons.
Core Documentation
Lecture notes by the teacherType of evaluation
The written test consists in drawing up a report in which the student shows how he has analyzed and discussed some geophysical data, also in relation to what he learned during the lectures. The oral exam focuses on the discussion of the report presented by the student and on the topics covered during the course. teacher profile teaching materials
Complex numbers and trigonometric functions; phasors.
Introduction to signal analysis; definition of a linear time-invariant system; convolution theorem.
Vector calculus; representation in polar, spherical and curvilinear coordinates.
Wave propagation; standing waves.
Fourier series and transform; Nyquist–Shannon sampling theorem.
Introduction to Python programming and exercise on the topics covered in the theory lessons.
Fruizione: 20410907 ANALISI DEI DATI NELLE GEOSCIENZE in Geologia e Tutela dell'Ambiente LM-74 LAURO SEBASTIAN EMANUEL
Programme
Matrix calculus and linear systems; matrix factorization (eigenvalues, eigenvectors); rigid rototranslations and associated matrix; least squares method and polynomial regression.Complex numbers and trigonometric functions; phasors.
Introduction to signal analysis; definition of a linear time-invariant system; convolution theorem.
Vector calculus; representation in polar, spherical and curvilinear coordinates.
Wave propagation; standing waves.
Fourier series and transform; Nyquist–Shannon sampling theorem.
Introduction to Python programming and exercise on the topics covered in the theory lessons.
Core Documentation
Lecture notes by the teacherType of evaluation
The written test consists in drawing up a report in which the student shows how he has analyzed and discussed some geophysical data, also in relation to what he learned during the lectures. The oral exam focuses on the discussion of the report presented by the student and on the topics covered during the course.