# UG Courses Mathematics

#### B. Tech. core courses New Curriculum

MA101 Calculus (3) (3-1-0-5)

Single Variable Calculus: Limits and continuity of single variable functions, differentiation and applications of derivatives, Definite integrals, fundamental theorem of calculus, Applications to length, moments and center of mass, surfaces of revolutions, improper integrals, Sequences, series and their convergence, absolute and conditional convergence, power series. Taylor’s and Maclaurin's series.
Multi-variable Calculus: Functions of several variables-limits and continuity, partial derivatives, chain rule, gradient, directional derivatives, tangent planes, normals, extreme values, saddle points, Lagrange multipliers. Taylor’s formula. Double and triple integrals with applications, Jacobians, change of variables, line integrals, divergence, curl, conservative fields, Green’s theorem, surface integrals, Stokes’s Gauss Divergence theorem.

MA102 Linear Algebra, Integral Transforms and Special Functions (3) (3-1-0-5)

Linear Algebra : Vector spaces over R and C, Subspaces, Basis and Dimension, Matrices and determinants, Rank of a matrix, System of linear equations, Gauss elimination method, Linear transformations, Rank-nullity theorem, Change of basis, Eigen values, Eigen vectors, Diagonalization of a linear operator, Inner product spaces. Spectral theorem for real symmetric matrices, application to quadratic forms.
Integral Transforms: Laplace transforms of elementary functions, Inverse Laplace transforms and applications, Fourier series, Fourier transforms, Fourier cosine and sine integrals, Dirichlet integral, Inverse Fourier transforms, Special Functions: Gamma and Beta functions, Error functions.

MA103 Differential Equations (3)( 3-1-0-5)

Ordinary Differential Equations: First Order Equation, Exact equations, integrating factors and Bernoulli equations. Lipschitz condition, examples on non-uniqueness. Second order differential equations with constant coefficients: homogeneous and non-homogeneous differential equations. Wronskian and linear independence of solutions, method of variation of parameters. Cauchy-Euler equations, method to second order equations with variable coefficients, Some applications, Solution of IVP using Laplace Transform and Euler’s Method. Series solutions, Frobenius method, Legendere and Bessel equations, orthogonal properties of Legendre polynomials.
Partial Differential Equations: Linear second order partial differential equations and their classification, heat equation, vibrating string, Laplace equation; method of separation of variables.

MA104 Probability and Statistics (3)(3-0-0-6)

Probability: Axioms of probability, conditional probability, independence of two or more events, Bayes’ theorem. Random variable, distribution functions, standard probability distributions and their properties, Simulation. Multiple random variables, marginal and conditional probability distribution, independence of random variables, bivariate normal and multinomial distributions. Functions of random variables, covariance and correlation. Conditional expectation, sum of random number of independent random variables. Convergence in probability, laws of large numbers and central limit theorem.
Statistics: Sample, population, sampling techniques, descriptive statistics, popular sampling distributions. Point estimation, parameter estimation with MLE, interval estimation, hypothesis testing. Ordinary least Squares (OLS) regression, assumptions and limitations of OLS, inference concerning regression parameters, other regressions. Analysis of variance.

MA105 Probability and Stochastic Processes (3)( 3-1-0-5)

Probability: Axioms of probability, conditional probability, independence of two or more events, Bayes’ theorem. Random variable, distribution functions, standard probability distributions and their properties, Simulation. Multiple random variables, marginal and conditional probability distribution, independence of random variables, bivariate normal and multinomial distributions. Functions of random variables, covariance and correlation. Conditional expectation, sum of random number of independent random variables. Convergence in probability, laws of large numbers and central limit theorem.
Stochastic Processes: Introduction and motivation, classification of stochastic processes, Bernoulli process, Poisson process, Markov chains, single/multiple server queuing models, power spectral density

#### B. Tech. Elective courses

MAL451 Vector Field Theory, 2 (2-0-0)

Vector calculus, arc length, directional derivative, Differentiation and integration of vector valued functions, derivative of composite functions, vector equations:straightline, plane, space curves. Gradient, curl and divergence. Orthogonal Curvilinear coordinates, line, area and volume elements,expressions for gradient, curl and divergence. Line and double integrals, Green’s theorem, surface integrals, triple integrals, Stokes and divergence theorem swith applications. Conservative vector fields and path independence.

MAL452 Complex Analysis, 3 (3-0-0)

Limit, continuity and differentiability of functions of a  complex variable, analytic functions, Cauchy-  Riemann equations. Definition of integral, Cauchy  integral theorem, integral formula, derivatives of  analytic functions, Morera’s and Liouvile’s theorems,  maximum modulus principle. Poles and singularities,  Taylor’s and Laurent series, isolated singular points,  Cauchy residue theorem, evaluation of real integrals.  Conformal and bilinear mappings.

MAL453 Introduction to Functional Analysis, 3 (2-1-0)

Calculus of variations and applications. Normed linear  spaces, Banach spaces, Hahn-Banach Theorem.  Open mapping theorem, principle of uniform  bounded, Hilbert Spaces. Orthogonal projections,  self-adjoint, unitary and normal linear operators.  Orthogonal bases,Parseval’s relation and Bassel’s  inequality, Riesz representation theorem and Lax  Milgram Theorem.

MAL454 Modern Algebra, 3 (2-1-0)

Definition and example of groups, Lagrange theorem,  cyclic groups, linear groups, permutation groups.  Subgroups,normal subgroups,and factor groups,  Isomorphism theorems, Sylow theorems, and their  applications. Rings and fields.

MAL455 Operations Research, 3 (3-0-0)

Introduction to optimization, Formulation of linear  Optimization problems, Convexset, Linear  Programming model, Graphical method, Simplex  method, Finding a feasible basis – Big M and two  phase Simplex method, Duality in Linear Program.  Primal-dual relationship & economic interpretation of  Duality. Dual Simplex Algorithm. Sensitivity analysis.  Network analysis: Transportation & Assignment  problem, Integer programming problem: Formulation,  Branch & Boundand Cutting Plane methods,  Dynamic Programming (DP); Non-linear  Programming, Lagrange multipliers and Kuhn-Tucker  conditions.

MAL456 Fuzzy Logic And Applications, 3 (3-0-0)

Introduction: Information and Uncertainty, Classical/  Crisp set theory, Fuzzy set theory, Set theoretic  operations: t-norm and t-conorm, Fuzzy relations,  Fuzzy Arithmetic: Fuzzy number and fuzzy  equations, Fuzzification and defuzzyfication,  Propositional and predicate logic, Fuzzy rule base  and approximate reasoning, Fuzzy logic,  Applications , switching circuit and Boolean Algebra.

#### B. Tech. core courses Old Curriculum

MAL111 Mathematics Laboratory, 2 (1-0-2)

Rank of a matrix, consistent linear system of equations, row reduced echelon matrices, inverse of a matrix, Gauss- Jordan method of finding an inverse of a matrix.

##### Math software Tools Practice Sheet No.1

Eigen values and eigen vectors, diagonalisation of matrices, Caley-Hamilton theorem.

##### Math software Tools Practice Sheet No.2

Hermitian, Unitary and Normal Matrices, bilinear and quadratic forms.

##### Math software Tools Practice Sheet No.3

Roots of a polynomial; numerical solution of a System of algebraic equations:Newton-Raphsonand iterative methods;interpolation:Lagrange interpolation formula, interpolation formula by use of differences.

##### Math software Tools Practice Sheet No.4

Numerical differentiation; numerical integration: Trapezoidal rule and Simson’s formula; error estimates in numerical differentiation and integration.

##### Math software Tools Practice Sheet No.5

Computer graphics:plotting of line, triangle and circle; plotting of cylinder, cube and sphere; projections; rotations.

Calculus of functions of several variables,implicit functions,partial derivatives and total differentials, equality of mixed derivatives of composite functions, Taylor’s Theorem, Maxima and Minima,constrained extrema, Lagrange multipliers.Definite integrals, differentiation under integral sign, differentiation of integral swith variable limits, improper integral, Beta and Gamma functions. Multiple integrals:definitions, properties and evaluation of multiple integrals, application of double integrals (in Cartesian and polar coordinates), change of coordinates, Jacobian, line integrals, Green’s theorem, proof, first and second forms. Solution of first order differential equations. Existence and uniqueness of solution, Picard’s method of successive approximations.

MAL114 Linear Algebra, 3 (2-0-2)

Vector spaces, bases and dimensions, linear transformations, matrix of linear transformations, change of bases, inner product space, Graham- Schmidt orthogonalization. Triangular form, matrix norms Conditioning of linear systems, Singular Value decomposition. Direct methods:Gauss, Cholesky and Householder’s methods. Matrix iterative methods: Jacobi, Gauss-Siedel and relaxation methods, conjugate gradient methods and its pre- conditioning. Computation of eigen values and eigen vectors: Jacobi, Givens, Householder, QR and inverse methods.

MAL115 Real Analysis, 2 (2-0-0)

Product of sets, mappings and their compositions, Denumerable sets,upper and lower bounds, supremum and infimum. Metric spaces Definition and examples, open closed and bounded set, interior boundary, convergence and limit of a sequence. Cauchy sequence, completeness, Bolzano-Weierstrass theorem, continuity, intermediate value theorem, and uniform continuity, connectedness, compactness and separability. Integration Riemann sums, Riemann integral of a function, integrability of a function on a closed interval, mean value theorem, improper integrals. Fourier Series, Fourier Integrals and Fourier Transforms.

MAL116 Introduction to Ordinary Differential Equations, 3 (3-0-0)

Second order differential equations with constant Coefficients homogeneous and non-homogeneous differential equations, method of undetermined coefficients, annihilation method, method of variation of parameters. Wronskian and linear independence of solutions, solution of ODE by Laplace transform. Second order equations with Variable coefficients, Euler equation, linearly Independent solutions, solution of second order Equation with one known solution, application of Variations of parameters method to second order Equations with variable coefficients, Series solutions, Frobenius method, Legendere and Bessel equations, orthogonal properties of Legendre polynomials. Higher order differential equations. Boundary Value Problems and Strum-Liouville Theory: Two point boundary value problems, Strum- Liouville boundary value problems, non- homogeneous boundary value problems; series of orthogonal functions, mean convergence.

MAL213 Introduction to Probability Theory and Stochastic Processes, 3 (3-0-0)

Axioms of probability, conditional probability,  probability space, random variable, distribution  functions, standard probability distribution functions.  Multidimensional random variables, marginal and  conditional probability distribution, independence of  random variables, bivariate, normal and multinomial  distributions. Functions of several random variables,  expectation, moments and moment generation  functions, correlation, moment inequalities.  Conditional expectation and regression, random  sums, convergencein probability,  weak law of large  number and central limit theorem. Markov chains and  random processes: Markov and other stochastic  processes, stationary distributions and limit theorem,  reversibility, branching processes and birth- death  processes, Markov chains Monte Carlo. Queues:  Single-server queues, M/M1, M/G/1, G/M/1, and  G/G/1 queues.