MATHEMATICAL ANALYSIS B
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- Assessment methods
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Mathematical analysis A
Written exam with practical and theoretical questions. Possible discussion and oral examination of theoretical topics related to the written test.
Final vote in thirtieths as acquired from review of the written test, or after the oral examination, if required.
Learning basic tools in Linear Algebra and multivariable Calculus. In particular, we introduce linear complex spaces, the algebra of matrices, representations of linear functions between linear spaces, connections with solvability of linear systems and change of variables. This language is then applied to study multivariable functions, local and global properties, polynomial approximation. Optimization problems also with constraint. We introduce the Riemann integral for multivariable functions and develop calculus methods and applications. We finally introduce vector fields with applications to the Gauss principle.
The complex field, algebraic properties. Linear spaces, basis and dimension: scalar product, triangular inequality, Cauchy-Schwarz inequality, orthonormal basis and Gram-Schmidt procedure, projections theorem. Linearity: approximation and the superposition principle, the vector space Mat(m,n), row-column product, transpost, diagonal, triangular, and symmetric matrices, rotations in the plane, representation theorem, linear maps between finite dimensional vector spaces, composition of linear maps. Determinants, Laplace theorem and properties. Binet formula, rank of a matrix, kernel and rank of linear maps, nullstellensatz theorem. Inverse of a matrix and applications to linear systems of equations, Touche-Capelli theorem. Eigenvalues and eigenvectors, diagonalization. Real functions of several variables, level curves, limits and continuity, properties. Directional derivatives, linear approximation and the tangent plane, differentiability and the gradient formula. Optimization and the method of restrictions, the increment method. Fermat's theorem, higher order derivatives, Schwarz theorem, the chain rule, taylor expansion. The Hessian matrix. Constrained optimization, the Lagrange multiplier theorem. Surfaces, vector fields and the Jacobian matrix, coordinates transformations in the plane and in the space. Curve integrals and vector fields, conservative and local conservatives fields. Divergence, Curl, Laplacian and differential identities. Multiple integrals, Riemann sums and integrability of continuous functions, simple domains and iterated integrals. Properties of the Riemann integral, change of variables in double and triple integrals, polar coordinates, spherical and elliptic coordinates. Surface integrals, the divergence theorem, the Stoke theorem. The complex field: Gauss' plane, operations, algebraic and trigonometric form of complex numbers, De Moire formula, theorem on roots of complex numbers, the fundamental theorem of Algebra, subsets of the Gauss plane. Linear spaces, basis and dimension: scale product, triangular inequality, Cauchy-Schwarz inequality, orthonormal basis and Gram-Schmidt procedure, projections theorem. Linearity: approximation and the superposition principle, the vector space Mat(m,n), row-column product, transpost, diagonal, triangular, and symmetric matrices, rotations in the plane, representation theorem, linear maps between finite dimensional vector spaces, composition of linear maps. Determinants, Laplace theorem and properties. Binet formula, rank of a matrix, kernel and rank of linear maps, nullstellensatz theorem. Inverse of a matrix and applications to linear systems of equations, Touche-Capelli theorem. Eigenvalues and eigenvectors, diagonalization. Real functions of several variables, level curves, limits and continuity, properties. Directional derivatives, linear approximation and the tangent plane, differentiability and the gradient formula. Optimization and the method of restrictions, the increment method. Fermat's theorem, higher order derivatives, Schwarz theorem, the chain rule, taylor expansion. The Hessian matrix. Constrained optimization, the Lagrange multiplier theorem. Surfaces, vector fields and the Jacobian matrix, coordinates transformations in the plane and in the space. Curve integrals and vector fields, conservative and local conservatives fields. Divergence, Curl, Laplacian and differential identities. Multiple integrals, Riemann sums and integrability of continuous functions, simple domains and iterated integrals. Properties of the Riemann integral, change of variables in double and triple integrals, polar coordinates, spherical and elliptic coordinates. Surface integrals, the divergence theorem, the Stokes' theorem.
Bramanti, M., Pagani, C.D., Salsa, S.: Matematica Calcolo Infinitesimale e Algebra Lineare, Zanichelli;
R. Adams, Calculus: A Complete Course (7th Edition), Pearson.
Frontal lessons. Exercises in classroom and homework
Lecture notes possibly available through the e-learning platform