University of Mumbai Syllabus For Semester 3 (SE Second Year) Applied Mathematics 3: Knowing the Syllabus is very important for the students of Semester 3 (SE Second Year). Shaalaa has also provided a list of topics that every student needs to understand.
The University of Mumbai Semester 3 (SE Second Year) Applied Mathematics 3 syllabus for the academic year 2022-2023 is based on the Board's guidelines. Students should read the Semester 3 (SE Second Year) Applied Mathematics 3 Syllabus to learn about the subject's subjects and subtopics.
Students will discover the unit names, chapters under each unit, and subtopics under each chapter in the University of Mumbai Semester 3 (SE Second Year) Applied Mathematics 3 Syllabus pdf 2022-2023. They will also receive a complete practical syllabus for Semester 3 (SE Second Year) Applied Mathematics 3 in addition to this.
University of Mumbai Semester 3 (SE Second Year) Applied Mathematics 3 Revised Syllabus
University of Mumbai Semester 3 (SE Second Year) Applied Mathematics 3 and their Unit wise marks distribution
University of Mumbai Semester 3 (SE Second Year) Applied Mathematics 3 Course Structure 2022-2023 With Marking Scheme
| # | Unit/Topic | Weightage |
|---|---|---|
| 100 | Module 1 The Laplace Transform | |
| 200 | Module 2 Matrices | |
| 300 | Module 3 Complex Analysis | |
| 400 | Module 4 Cauchy’S Formula and Theorem | |
| 500 | Module 5 Statistics | |
| 600 | Module 6 Optimization | |
| Total | - |
Syllabus
- The Laplace transform:- Definition and properties (without proofs); all standard transform methods for elementary functions including hyperbolic functions; Heaviside unit step function, Dirac delta function; the error function; evaluation of integrals using Laplace transforms; inverse Laplace transforms using partial fractions and H(t-a); convolution (no proof).
- Matrices:-
- Eigenvalues and eigenspaces of 2x2 and 3x3 matrices;
- existence of a basis and finding the dimension of the eigenspace (no proofs);
- nondiagonalisable matrices; minimal polynomial;
- Cayley - Hamilton theorem (no proof); quadratic forms;
- orthogonal and congruent reduction of a quadratic form in 2 or 3 variables; rank, index, signature; definite and indefinite forms.
- Complex analysis:-
- Cauchy-Riemann equations (only in Cartesian coordinates) for an analytic function (no proof);
- harmonic function;
- Laplace’s equation;
- harmonic conjugates and orthogonal trajectories (Cartesian coordinates); to find f(z) when u+v or u - v are given;
- Milne-Thomson method; cross-ratio (no proofs);
- conformal mappings; images of straight lines and circles.
- Complex Integration Cauchy’s integral formula; poles and residues;
- Cauchy’s residue theorem;
- applications to evaluate real integrals of trigonometric functions;
- integrals in the upper half plane; the argument principle.
- Statistics:
- (No theory questions expected in this module) Mean, median, variance, standard deviation;
- binomial, Poisson and normal distributions;
- correlation and regression between 2 variables.
- Non-linear programming:-
- Lagrange multiplier method for 2 or 3 variables with at most 2 constraints;
- conditions on the Hessian matrix (no proof);
- Kuhn-Tucker conditions with at most 2 constraints.
