Courses
- Fundamentals of Computer Science and Data (7204)
- Fundamentals of Computer Science and Data1 (7214)
- Differential and Integral Calculus1 (90901) תקציר הקורס:
- Differential and Integral Calculus2 (90902) תקציר הקורס:
- Linear Algebra (90905) תקציר הקורס:
- Ordinary Differential Equations (90914) תקציר הקורס:
- Harmonic Analysis (90916) תקציר הקורס:
- Complex Functions (90917) תקציר הקורס:
- Discrete Mathematics (90926) תקציר הקורס:
- Discrete Mathematics IBL (90955) תקציר הקורס:
Abstract:
Real numbers. Sequences. Limit of a sequence. Limits and continuity of f?unctions. Intermediate value theorem. Weierstrass's theorem. The derivative. Techniques of differentiation. Fermat, Rolle and Lagrange theorems. L'H?pital's rule. Taylor polynomial approximations. The derivative in graphing and applications. The definite and indefinite integral. Principles on integral evaluation: integration by parts and by substitution. The fundamental theorem of calculus (Newton-Leibniz). Improper integral.Abstract:
Infinite series. Convergence tests. Series of f?unctions; convergence and uniform convergence. Power series; representation of f?unctions by power series. Taylor series. F?unctionsof several variables- limits and continuity, partial and directional derivatives, Linear approximation, Gradient. The chain rule. Higher order partial derivatives and second degree Taylor polynomial. Relative/absolute maximum and minimum values. Lagrange multipliers. Multiple integrals. Fubini's theorem. Change of variables. Polar, cylindrical and spherical coordinates. Line integrals of scalar f?unctions. Line integrals of vector fields. Independence of path and Green theorem. Surface integrals of scalar f?unctions. Oriented surfaces and surface integrals of vector fields. The divergence theorem (Gauss-Ostrogradsky). Stokes' theorem. Applications.Abstract:
The first part of the course is dedicated to study of techniques for
solving systems of linear equations. Several basic methods are presented:
Gauss elimination, matrix solution, Cramer rule.
The last two methods involve matrix arithmetic, which is also presented in this part. The second part discusses vector spaces and linear transformations. Most attention is given to the matrix approach. Matrix diagonalization issues summarize this part.
The last part of the course study inner product spaces and their basic properties.Abstract:
Sorting differential equations.
First-order differential equations.
Linear differential equations of order n:
homogeneous and non-homogeneous equation, Wronskian homogeneous equations with constant
coefficients. Separation into homogeneous and non-homogeneous problem,
method of unknown coefficients and method of variation of parameters.
Language Problems - Sturm Liouville Theory: Defining a close-knit operator,
finding the operator's self-values and self-func tions and proving their properties.
System of Linear Differential Equations Order 1: Solving the homogeneous
system using eigenvalues and eigenvectors of the matrix.
The Wronskian of the system. The non-homogeneous system.Abstract:
Fourier series: expansion to Fourier series on a finite interval,
Fourier coefficients. Complex representation of Fourier series,
the convergence of the series, Dirichlet func tion,
convergence in a jump discontinuity. Gibbs phenomena.
Parseval’s identity. Differentiation and integration of Fourier series.
Fourier transform, definition, properties and the transform table.
Applications of Fourier transform in signal processing and
in solutions of differential equations. Laplace transform and its applications
in solving ordinary differential equations.
Solution in cases where the forcing term is a step func tion or a delta func tion.Abstract:
Complex integration : Contour Integrals. Residue theory.
Cauchy’s Residue Theorem and its applications: evaluation of integrals.