03KXTLI, 03KXTJM, 03KXTLM, 03KXTLP, 03KXTLS, 03KXTLX, 03KXTLZ, 03KXTMA, 03KXTMB, 03KXTMC, 03KXTMH, 03KXTMK, 03KXTMO, 03KXTMQ, 03KXTNX, 03KXTOD, 03KXTPC, 03KXTPI, 03KXTPL

A.A. 2018/19

Course Language

Inglese

Course degree

1st degree and Bachelor-level of the Bologna process in Ingegneria Dell'Autoveicolo (Automotive Engineering) - Torino

1st degree and Bachelor-level of the Bologna process in Ingegneria Meccanica (Mechanical Engineering) - Torino

1st degree and Bachelor-level of the Bologna process in Ingegneria Informatica (Computer Engineering) - Torino

1st degree and Bachelor-level of the Bologna process in Electronic And Communications Engineering (Ingegneria Elettronica E Delle Comunicazioni) - Torino

1st degree and Bachelor-level of the Bologna process in Ingegneria Dei Materiali - Torino

1st degree and Bachelor-level of the Bologna process in Ingegneria Elettrica - Torino

1st degree and Bachelor-level of the Bologna process in Ingegneria Aerospaziale - Torino

1st degree and Bachelor-level of the Bologna process in Ingegneria Biomedica - Torino

1st degree and Bachelor-level of the Bologna process in Ingegneria Chimica E Alimentare - Torino

1st degree and Bachelor-level of the Bologna process in Ingegneria Civile - Torino

1st degree and Bachelor-level of the Bologna process in Ingegneria Edile - Torino

1st degree and Bachelor-level of the Bologna process in Ingegneria Energetica - Torino

1st degree and Bachelor-level of the Bologna process in Ingegneria Per L'Ambiente E Il Territorio - Torino

1st degree and Bachelor-level of the Bologna process in Matematica Per L'Ingegneria - Torino

1st degree and Bachelor-level of the Bologna process in Ingegneria Elettronica - Torino

1st degree and Bachelor-level of the Bologna process in Ingegneria Fisica - Torino

1st degree and Bachelor-level of the Bologna process in Ingegneria Del Cinema E Dei Mezzi Di Comunicazione - Torino

1st degree and Bachelor-level of the Bologna process in Ingegneria Gestionale - Torino

1st degree and Bachelor-level of the Bologna process in Ingegneria Gestionale - Torino

Course structure

Teaching | Hours |
---|---|

Lezioni | 60 |

Esercitazioni in aula | 30 |

Esercitazioni in laboratorio | 10 |

Teachers

Teacher | Status | SSD | h.Les | h.Ex | h.Lab | h.Tut | Years teaching |
---|---|---|---|---|---|---|---|

Carlini Enrico - Corso 1 | Professore Ordinario | MAT/03 | 40 | 20 | 0 | 0 | 6 |

Carlini Enrico - Corso 2 | Professore Ordinario | MAT/03 | 40 | 20 | 0 | 0 | 6 |

Teaching assistant

Context

SSD | CFU | Activities | Area context |
---|---|---|---|

MAT/03 MAT/08 |
7 3 |
A - Di base A - Di base |
Matematica, informatica e statistica Matematica, informatica e statistica |

2018/19

The course has two main goals. The first one is to introduce the main topics of linear algebra and geometry, training the student to follow logical deductive arguments and to use the proper formal language. The second goal is to give to the students the main concepts of some basic numerical methods of linear algebra and of their implementation in MATLAB, which is by now widely used in engineering. The course will show how theoretic, symbolic and numerical aspects interact with each other.

The course has two main goals. The first one is to introduce the main topics of linear algebra and geometry, training the student to follow logical deductive arguments and to use the proper formal language. The second goal is to give to the students the main concepts of some basic numerical methods of linear algebra and of their implementation in MATLAB, which is by now widely used in engineering. The course will show how theoretic, symbolic and numerical aspects interact with each other.

This course wants to develop the student's ability to understand logical arguments stressing the role of the hypothesis, for example by building examples and counterexamples. The student acquires tools and techniques to work with geometrical objects (vectors in the plane and i the space, lines, planes, conics and quadrics) and with algebraic objects (linear systems of equations, matrices, polynomials, eigenvalues, eigenvectors, vector spaces and their transformations). For example, the student is able to symbolically deal with a linear system of equations and to compute its solutions: these solutions can correspond to the intersection of two lines, to the eigenvectors of a matrix or to the circles passing through two points. The student will also acquire the necessary knowledge to numerically solve some basic problems in linear algebra (for example, computing the solutions of a linear system of equations and computing the eigenvalues of a matrix). These problems usually arise as an intermediate, or final, step in solving more complex problems which can not be treated with analytical methods. In particular, the student learns to identify, among the presented methods the one giving the most accurate solution with the least computational cost. The use of the software MATLAB is crucial to reach these goals.

This course wants to develop the student's ability to understand logical arguments stressing the role of the hypothesis, for example by building examples and counterexamples. The student acquires tools and techniques to work with geometrical objects (vectors in the plane and i the space, lines, planes, conics and quadrics) and with algebraic objects (linear systems of equations, matrices, polynomials, eigenvalues, eigenvectors, vector spaces and their transformations). For example, the student is able to symbolically deal with a linear system of equations and to compute its solutions: these solutions can correspond to the intersection of two lines, to the eigenvectors of a matrix or to the circles passing through two points. The student will also acquire the necessary knowledge to numerically solve some basic problems in linear algebra (for example, computing the solutions of a linear system of equations and computing the eigenvalues of a matrix). These problems usually arise as an intermediate, or final, step in solving more complex problems which can not be treated with analytical methods. In particular, the student learns to identify, among the presented methods the one giving the most accurate solution with the least computational cost. The use of the software MATLAB is crucial to reach these goals.

A working knowledge of the mathematical tools presented in the first semester. In particular, a basic knowledge of real and complex numbers, solving equations and inequalities of degree one or two, differential and integral calculus as given in Mathematical Analysis I, as well as the main syntactic constructs used in computer programming, taught in the course of Computer Sciences

A working knowledge of the mathematical tools presented in the first semester. In particular, a basic knowledge of real and complex numbers, solving equations and inequalities of degree one or two, differential and integral calculus as given in Mathematical Analysis I, as well as the main syntactic constructs used in computer programming, taught in the course of Computer Sciences

• Vector in 2-space and in 3-space and their operations. Dot product, cross product and box product. Lines and planes in 3-space. Orthogonal projections.
• Matrices and their operations. Strongly reduced matrices. Matrix form of linear systems of equations and their solutions with geometrical applications. Matrix equations and inverse of a matrix. Determinants.
• Vector spaces: definition, examples and applications. Sub-vector spaces and main operations with them.
• Linear combination and linearly dependent vectors. How to extract linearly independent vectors from a set. Bases of a vector space. Dimension of a vector space. Dimension of finitely generated subspace.
• Space of polynomials. Grassmann's relation.
• Linear maps. Image of a linear map. Injective and surjective linear maps. Isomorphisms.
• Matrix of a linear map. Endomorphism and square matrices.
• Eigenvalues and eigenvectors. Eigenspaces of matrix endomorphisms. Characteristic polynomial of an endomorphism. Diagonalization of and endomorphism.
• Orthonormal bases, orthonormal matrices. Gram-Schmidt's algorithm. Diagonalization of real symmetric matrices using orthogonal matrices. Quadratic forms and the sign that they can take in a point.
• Metric problems: distance between two points, two lines, and a point and a line.
• Quadratic geometry: conic curves, and spheres. Non-degenerate quadrics in canonical form. Recognising a quadric surface.
•Machine arithmetic, machine numbers, rounding error. Conditioning of a numerical problems, Stabilty of an algorithm.
•Approximation of functions and data : polynomial interpolation and piecewise polynomial interpolation (spline). Convergence.
•Linear systems: conditioning and numerical direct method. Matrix factorizations PA=LU, Choleski, QR and their main applications.
•Eigenvalues of matrices: conditioning and numerical methods (powers, inverse power, QR (basics notions)). Singular values decomposition of matrices and its applications.
Practical sessions
Practical sessions will work on the arguments of the lectures. Some practical sessions will be held by the teaching assistant solving problems and some will require the active participation of the students. Moreover, there will be computer aided sessions in which the methods presented during the lectures will be used with the help of the software MATLAB. The goal of the practical sessions is a better understanding of the methods presented during the lectures and to give a critical analysis of the obtained solutions.

• Vector in 2-space and in 3-space and their operations. Dot product, cross product and box product. Lines and planes in 3-space. Orthogonal projections.
• Matrices and their operations. Strongly reduced matrices. Matrix form of linear systems of equations and their solutions with geometrical applications. Matrix equations and inverse of a matrix. Determinants.
• Vector spaces: definition, examples and applications. Sub-vector spaces and main operations with them.
• Linear combination and linearly dependent vectors. How to extract linearly independent vectors from a set. Bases of a vector space. Dimension of a vector space. Dimension of finitely generated subspace.
• Space of polynomials. Grassmann's relation.
• Linear maps. Image of a linear map. Injective and surjective linear maps. Isomorphisms.
• Matrix of a linear map. Endomorphism and square matrices.
• Eigenvalues and eigenvectors. Eigenspaces of matrix endomorphisms. Characteristic polynomial of an endomorphism. Diagonalization of and endomorphism.
• Orthonormal bases, orthonormal matrices. Gram-Schmidt's algorithm. Diagonalization of real symmetric matrices using orthogonal matrices. Quadratic forms and the sign that they can take in a point.
• Metric problems: distance between two points, two lines, and a point and a line.
• Quadratic geometry: conic curves, and spheres. Non-degenerate quadrics in canonical form. Recognising a quadric surface.
•Machine arithmetic, machine numbers, rounding error. Conditioning of a numerical problems, Stabilty of an algorithm.
•Approximation of functions and data : polynomial interpolation and piecewise polynomial interpolation (spline). Convergence.
•Linear systems: conditioning and numerical direct method. Matrix factorizations PA=LU, Choleski, QR and their main applications.
•Eigenvalues of matrices: conditioning and numerical methods (powers, inverse power, QR (basics notions)). Singular values decomposition of matrices and its applications.
Practical sessions
Practical sessions will work on the arguments of the lectures. Some practical sessions will be held by the teaching assistant solving problems and some will require the active participation of the students. Moreover, there will be computer aided sessions in which the methods presented during the lectures will be used with the help of the software MATLAB. The goal of the practical sessions is a better understanding of the methods presented during the lectures and to give a critical analysis of the obtained solutions.

Lectures (60%) and practical sessions (30%+10%)

Lectures (60%) and practical sessions (30%+10%)

On the portale della didattica will be available didactical material prepared by the instructors including theory, solved and proposed exercises.
Reference texts:
M. Ferrarotti, M. Abrate “Lezioni di Algebra Lineare”, CELID, 2018.
M. Ferrarotti, M. Abrate “Lezioni di Geometria”, CELID, 2018.
L. Gatto, Lezioni di Algebra lineare e Geometria, CLUT, 2018.
S. Greco, P. Valabrega, Lezioni di Geometria, Vol. 1 Algebra lineare, Vol. 2 Geometria Analitica, Ed. Levrotto e Bella, Torino 2009.
G. Monegato, Metodi e algoritmi per il Calcolo Numerico, CLUT, 2008.
A. Quarteroni, F. Saleri, P. Gervasio, Scientific Computing with MATLAB and OCTAVE, Springer, 2014.
G. Strang, Algebra Lineare, Apogeo, 2008.
G. Strang, Introduction to Linear Algebra, Wellesley-Cambridge Press, 2016.
E. Carlini, LAG: the written exam, CLUT 2019.
E. Carlini, 50 multiple choices in Geometry, CELID 2011.
G. Casnati, M.L. Spreafico, Allenamenti di Geometria, Ed. Esculapio, Bologna 2013.
J. Cordovez, Chissà chi lo sa?, CLUT 2013.
L. Scuderi, Laboratorio di Calcolo Numerico, CLUT, 2005.

On the portale della didattica will be available didactical material prepared by the instructors including theory, solved and proposed exercises.
Reference texts:
M. Ferrarotti, M. Abrate “Lezioni di Algebra Lineare”, CELID, 2018.
M. Ferrarotti, M. Abrate “Lezioni di Geometria”, CELID, 2018.
L. Gatto, Lezioni di Algebra lineare e Geometria, CLUT, 2018.
S. Greco, P. Valabrega, Lezioni di Geometria, Vol. 1 Algebra lineare, Vol. 2 Geometria Analitica, Ed. Levrotto e Bella, Torino 2009.
G. Monegato, Metodi e algoritmi per il Calcolo Numerico, CLUT, 2008.
A. Quarteroni, F. Saleri, P. Gervasio, Scientific Computing with MATLAB and OCTAVE, Springer, 2014.
G. Strang, Algebra Lineare, Apogeo, 2008.
G. Strang, Introduction to Linear Algebra, Wellesley-Cambridge Press, 2016.
E. Carlini, LAG: the written exam, CLUT 2019.
E. Carlini, 50 multiple choices in Geometry, CELID 2011.
G. Casnati, M.L. Spreafico, Allenamenti di Geometria, Ed. Esculapio, Bologna 2013.
J. Cordovez, Chissà chi lo sa?, CLUT 2013.
L. Scuderi, Laboratorio di Calcolo Numerico, CLUT, 2005.

The exam will check both theoretical knowledge and practical skills acquired by the student. The exam will consist in a computer assisted test and in a written exam. During the test and the written exam it is forbidden to use books, notes and all not authorised material. The computer test consists of multiple choice questions, most of them to be solved using MATLAB. The computer test takes 45 minutes and contributes up to 30% of the final grade. Wrong answers are penalised. There exists a minimal threshold of correct answers under which the student cannot take the written exam and fails the exam. The written exam consists of multiple choices questions and one exercise. The written exam takes 1 hour and contributes up to 70% of the final grade. There exists a minimal threshold of correct answers under which the student fails the exam. An additional oral test can be sustained at the professor's discretion. To pass the exam, the student must attend both parts (computer assisted and written), score the minimal number of required points, and the sum of the two grades (computer assisted + written) must be at least 18.
More details will be given during the lectures and will be posted on the web page of the course.

© Politecnico di Torino

Corso Duca degli Abruzzi, 24 - 10129 Torino, ITALY

Corso Duca degli Abruzzi, 24 - 10129 Torino, ITALY