Random fluctuations, which can also be interpreted as noise, are added to an ordinary differential equation. This results in stochastic differential equations, whose solutions represent random processes. Application areas of this type of differential equation include financial mathematics (modeling stock prices and the resulting option pricing), laser physics, climate models, and others. This lecture covers the associated theory (definition, existence, uniqueness) and numerical solution methods for stochastic differential equations.
This course provides an introduction to numerical mathematics. The topics are computer arithmetic, error analysis, linear systems of equations, linear regression, polynomial interpolation, spline interpolation, quadrature, nonlinear systems of equations.
This course covers numerical methods for solving initial value problems in ordinary differential equations. Topics include single-step methods, multi-step methods, and methods for stiff differential equations.
Numerics 1: This course provides an introduction to numerical mathematics. The topics are computer arithmetic, error analysis, linear systems of equations, linear regression, polynomial interpolation, spline interpolation, quadrature, nonlinear systems of equations.
Statistics 1: Basic concepts, statistical graphics, statistical tests, simple regression, contingency tables.
Teaching Assistant for National Programme on Technology Enhanced Learning (NPTEL) courses:
Roll: Teaching Assistant.
1) Scientific computing using MATLAB
2) Introduction to methods of applied mathematics
3) Matrix Computation and its applications