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Glossary
Semester (Sem)
1First Semester
2Second Semester
AAnnual course
Educational activities
ABasic activities
Language
Course completely offered in italian
Course completely offered in english
--Not available
Innovative teaching
The credits shown next to this symbol indicate the part of the course CFUs provided with Innovative teaching.
These CFUs include:
  • Subject taught jointly with companies or organizations
  • Blended Learning & Flipped Classroom
  • Massive Open Online Courses (MOOC)
  • Soft Skills
Course Details
Context
Academic Year 2015/2016
School School of Industrial and Information Engineering
Name (Bachelor of Science degree)(ord. 270) - MI (349) Electrical Engineering
Track R1L - elt
Programme Year 2

Course Details
ID Code 091185
Course Title ANALYTICAL AND STATISTICAL METHODS FOR ENGINEERS
Course Type Integrated Course
Credits (CFU / ECTS) 8.0
Semester Second Semester
Course Description 1 - Analytic functions: Cauchy-Riemann equations. Cauchy Theorem. Conformal mappings. Residue. Uniqueness of analytic extension. Multivalued functions. Computation of definite integrals. - Functional Analysis: Lebesgue Integral. Banach and Hilbert spaces. Ck and Lp spaces. H"older and Minkowski inequalities. Dirac Delta. Distributional derivative. Tempered distributions. Convolution. - Fourier Transform: Transform of L^1 and L^2 functions. Riemann-Lebesgue Lemma. Algebraic and functional properties of Fourier transform. Plancherel identity. Fourier transform of tempered distributions. Solution of differential equations. Fourier series and Fourier transform of comb signal. Periodic solutions of O.D.E. Shannon sampling Theorem. - Laplace Transform: Laplace transform of functions and distributions. Algebraic and functional properties of Laplace transform. Initial value Theorem. Final value Theorem. Solution of Cauchy problems. Delayed-time equations. - Partial Differential Equations: Boundary value problems: Dirichlet and Neumann conditions. Wave equation. D'Alembert formula. Vibrating string. Separation of variables. Radially symmetric domains. Rectangular domains. Eigenvalue problems. - Probability theory. Probability space and fundamental properties. Discrete (Bernoulli, Binomial, geometric, Poisson) and continuous (exponential, gaussian) random variables. Expected value, variance and quantiles. Law of large numbers and Central Limit theorem. - Inferential statistics. General estimators, estimators for the mean value and the variance. Confidence intervals and tests for the mean value and the variance. Test for the independence and goodness of fit. Difference between means and between matched pairs. - Descriptive statistics. Collections of data, frequencies. Mean value and variance. Graphical displays: diagrams and boxplots. Linear regression.
Scientific-Disciplinary Sector (SSD)
Educational activities SSD Code SSD Description CFU
A
MAT/05
MATHEMATICAL ANALYSIS
5.0
A
MAT/06
PROBABILITY AND STATISTICS
3.0

Schedule, add and removeAlphabetical groupCodeModule DescriptionProfessorCFUSem.LanguageCourse details
From (included)To (excluded)
--AZZZZ091178STATISTICSEpifani Ilenia3.02
091177MATHEMATICAL ANALYSIS IIITomarelli Franco5.02
manifesti v. 3.4.0 / 3.4.0
Area Servizi ICT
20/09/2020