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# Study Numerical Computing - MCA Subject

## STUDY - Numerical Computing

Note : Emphasis is on computational methods
Errors in Computer Arithmetic, Normalization.
Bisection, Falsiposition and Newton-Raphson methods for solution of nonlinear equations. Errors in the
solutions, Convergence of Solutions.
Gauss, Gauss-Siedel and Iterative methods for system of linear equations. Ill conditioned system, Pivotal
Condensation, Matrix Inversion, Eigen-values, Eigen-vector, Diagonalization of Real Symmetric Matrix by
Jacobi's Method.
Introduction to Finite Differences.
Polynomial Interpolation using Newton's and Lagrange's formulae.

## STUDY - Numerical Differentiation. Numerical Integration :

Trapezoidal Rule, Simpson's Rule, Weddle's Rule, Gauss

Quadrature Formula. Error in numerical Integration.

## STUDY - Numerical Solution of differential Equations:

Picards Method, Taylor’s Series Method, Euler’s Method,
Modified Euler’s Method, Runge-Kutta Method, Predictor-Corrector Method.

## MCA Subjects

 Advanced Computer Architecture Theory of Computation Advanced course in Software Engineering Advanced DBMS Artificial Intelligence Bioinformatics Algorithms Business Accounting Compiler Design Computer Graphics Computer Organization and Architecture Data and File Structures Data Communication and Computer Networks Database Management Systems Design Methods and Analysis of Algorithms Discrete Mathematical Structures Distributed Systems E commerce Information Retrieval and Web Mining Internals of UNIX OS and Network Programming Introduction to Computer Programming through C Introduction to Cryptography Numerical Computing Object Oriented Programming through JAVA Operating System Concepts Operation Research Parallel Computing Quantum Computing Science of Programming Simulation and Modeling Soft Computing Techniques Software Engineering

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