GATE ( Graduate Aptitude Test in Engineering ) is considered to be the standard examination conducted not only for post graduation admissions but also get opportunities to be placed in several Public Sector Units like BHEL, BEL, BSNL and research organizations. Based on the score achieved in GATE, admissions are offered in IITs, IISc, and NITs. Here we are giving you detailed GATE Syllabus for Electrical Engineering 2018.
We are providing you Subject Specialization Priority for easy study plan. You can prefer this main subjects for preparation which are having more weightage in paper. Gate syllabus for Electrical Engineering also includes subject specialization for reference is given as below.
Here we are providing detailed GATE Syllabus for Electrical Engineering 2018.There are total 10 sections in Gate syllabus for Electrical engineering. You have to prepare atleast 85% of total Syllabus for successful attempt of GATE .
Linear Algebra : Matrix Algebra, Systems of linear equations, Eigenvalues, Eigenvectors. Calculus: Mean value theorems, Theorems of integral calculus, Evaluation of definite and improper integrals, Partial Derivatives, Maxima and minima, Multiple integrals, Fourier series, Vector identities, Directional derivatives, Line integral, Surface integral, Volume integral, Stokes's theorem, Gauss's theorem, Green's theorem.
Differential Equations : First order equations (linear and nonlinear), Higher order linear differential equations with constant coefficients, Method of variation of parameters, Cauchy's equation, Euler's equation, Initial and boundary value problems, Partial Differential Equations, Method of separation of variables.
Complex Variables : Analytic functions, Cauchy's integral theorem, Cauchy's integral formula, Taylor series, Laurent series, Residue theorem, Solution integrals. Probability and Statistics: Sampling theorems, Conditional probability, Mean, Median, Mode, Standard Deviation, Random variables, Discrete and Continuous distributions, Poisson distribution, Normal distribution, Binomial distribution, Correlation analysis, Regression analysis.
Numerical Methods : Solutions of nonlinear algebraic equations, Single and Multi‐step methods for differential equations.