Jul 2—Oct 22, 2022
Integral Calculus and Ordinary Differential Equations for EE
Dr. Natalia Gulko
- The Riemann integral: Riemann sums, the fundamental theorem of calculus and the indefinite integral. Methods for computing integrals: integration by parts, substitution, partial fractions. Improper integrals and application to series. 2. Uniform and pointwise convergence. Cauchy criterion and the Weierstrass M-test. Power series. Taylor series. 3. First order ODE’s: initial value problem, local uniqueness and existence theorem. Explicit solutions: linear, separable and homogeneous equations, Bernoulli equations. 4. Systems of ODE’s. Uniqueness and existence (without proof). Homogeneous systems of linear ODE’s with constant coefficients. 5. Higher order ODE’s: uniqueness and existence theorem (without proof), basic theory. The method of undetermined coefficients for inhomogeneous second order linear equations with constant coefficients. The harmonic oscillator and/or RLC circuits. If time permits: variation of parameters, Wronskian theory.
Differential and Integral Calculus ME2
Dr. Irena Lerman
- Infinite series of nonnegative terms and general series. Absolute and conditional convergence. Power series.
- Vector algebra. Dot product, cross product and box product.
- Analytic geometry of a line and a plane. Parametric equations for a line. Canonic equations for a plane. Points, lines and planes in space.
- Vector-valued functions. Derivative. Parametrized curves. Tangent lines. Velocity and acceleration. Integration of the equation of motion.
- Surfaces in space. Quadric rotation surfaces. Cylindrical and spherical coordinates.
- Scalar functions of several variables. Scalar field. Level surfaces. Limit and continuity. Partial derivatives. Directional derivative. Gradient vector. Differential. Tangent plane and normal line. Chain rules. Implicit function and its derivative. Taylor and MacLaurin formulas. Local extreme values. Absolute maxima and minima on closed bounded regions.
- Vector-valued functions of several variables. Vector field. Field curves. Divergence and curl.
- Line and path integrals. Work, circulation. Conservative fields. Potential function.
- Double integral and its applications. Green’s theorem.
- Parametrized surfaces. Tangent plane and normal line. Surface integrals. Flux. Stokes’s theorem.
- Triple integral and its applications. Divergence theorem.
Linear Algebra for Electrical Engineering 2
יום א 14:00 - 10:00 in בניין כתות לימוד  חדר 117
Fields: the definition of a field, complex numbers.
Linear equations: elementary operations, row reduction, homogeneous and non-homogeneous equations, parametrization of solutions.
Vector spaces: examplex, subspaces, linear independence, bases, dimension.
Matrix algebra: matrix addition and multiplication, elementary operations, the inverse matrix, the determinant and Cramer’s law. Linear transformations: examples, kernel and image, matrix representation.
Fourier analysis for Electrical Engineering
Dr. Motke Porat
- Complex valued-functions and the complex exponential. Fourier coefficients of piecewise continuous periodic functions. Basic operations and their effects on Fourier coefficients: translation, modulation, convolutions, derivatives.
- Uniform convergence: Cesaro means, the Dirichlet and Fejer kernels, Fejer’s theorem. The Weierstrass approximation theorem for trigonometric polynomials and for polynomials. Uniqueness of Fourier coefficients. The Riemann-Lebesgue lemma. Hausdorff’s moment problem. Convergence of partial sums and Fourier series for $C^2$-functions.
- Pointwise convergence: Dini’s criterion. Convergence at jump discontinuities and Gibbs phenomenon.
- $L^2$-theory: orthonormal sequences and bases. Best approximations, Bessel’s inequality, Parseval’s identity and convergence in $L^2$.
- Applications to partial differential equations: the heat and wave equations on an interval with constant boundary conditions, the Dirichlet problem for the Laplace equation on the disk, the Poisson kernel.
- Korner, Fourier analysis
- Stein and Shakarchi, Fourier analysis
- Courses marked with (*) are required for admission to the M.Sc. program in Mathematics.
- The M.Sc. degree requires the successful completion of at least 2 courses marked (#). See the graduate program for details
- The graduate courses are open to strong undergraduate students who have a grade average of 85 or above and who have obtained permission from the instructors and the head of the teaching committee.
- Please see the detailed undergraduate and graduate programs for the for details on the requirments and possibilities for complete the degree.