Linear Algebra-I:
Introduction to vector spaces and sub-spaces, definitions, illustrative example. Linearly independent and dependent vectors- Basis-definition and problems. Linear transformationsdefinitions. Matrix form of linear transformationsIllustrative examples
Linear Algebra-II:
Computation of eigen values and eigen vectors of real symmetric matrices-Given’s method. Orthogonal vectors and orthogonal bases. Gram-Schmidt orthogonalization process.
Calculus of Variations:
Concept of functional-Eulers equation. Functional dependent on first and higher order derivatives, Functional on several dependent variables. Isoperimetric problemsvariation problems with moving boundaries.
Probability Theory:
Review of basic probability theory. Definitions of random variables and probability distributions, probability mass and density functions, expectation, moments, central moments, characteristic functions, probability generating and moment generating functions-illustrations. Poisson, Gaussian and Erlang distributionsexamples.
Engineering Applications on Random processes:
Classification. Stationary, WSS and ergodic random process. Auto-correlation functionproperties, Gaussian random process.