
MSRIT Numerical and Mathematical Biology Sem 3 Unit 1 : Numerical solution of Algebraic and Transcendental equations(Method of false position, Newton  Raphson method) 


1. Numerical Methods  I(Mathematics III) 
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In this chapter we first present some numerical methods of solving algebraic and transcendental equations. Then we consider the GaussSeidel method and the Relaxation method of solving systems of linear equations. Lastly, we consider the power method of finding the largest eigenvalue of a square matrix.
Title: Engineering Mathematics Part  III




2. Mathematical Modeling(Physics) 
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Algorithms, modeling and simulation in physics, Errors in numerical calculations, Roots of an equation : NewtonRaphson method and Bisection method. Application using Bisection method for LCR transient circuit (to determine R for given values of L and C for a prespecified rate of dissipation of energy), program in C
Title: Concise Physics BSc VI Semester Volume 8 (603)




3. Numerical Methods I(Mathematics) 
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In the process of analysing problems in engineering, the analysts come across systems of equations which belong to different categories like, linear algebraic, nonlinear, transcendental, differential and integral equations. School level mathematics and elementary engineering mathematics include, among other topics, solution aspects of certain simple classes of equations. But, in many contexts, it
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Title: Engineering Mathematics  III




4. Bisection Method and Iterative Methods of Transcendental Equations (Mathematics) 
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This unit deals with the definition of transcendental function and explains the Bisection Method, Secant and RegulaFalsi Methods and Newton Raphson Method. It also explains Muller method, Chebyshev method and describes the multipoint iteration methods to find roots of the equations.
Title: Math 2.4 Numerical Analysis




5. General Iterative Methods(Mathematics) 
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This unit defines iteration function and explains high order Methods. It also explains acceleration of the convergence and efficiency of a method and helps in analyzing system of nonlinear equations.
Title: Math 2.4 Numerical Analysis




6. Rate of Convergence of Iterative Methods(Mathematics) 
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This unit defines rate of convergence of an iterative method and explains rate of convergence of Secant and RegulaFalsi Methods, and Newton
Raphson Method. It also explains rate of convergence of Muller method and Chebyshev method.
Title: Math 2.4 Numerical Analysis




7. LOAD FLOW STUDIES(Electrical ) 
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The numerical analysis involving the solution of algebraic simultaneous equations forms the basis for solution of the performance equations in computer aided electrical power system analyses, such as during linear graph analysis, load flow analysis (nonlinear equations), transient stability studies (differential equations), etc.
Title: Computer Techniques in Power System Analysis
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8. Numerical Differentiation(Physics) 
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The method of finding derivatives analytically are well established when the functional relation between the dependent variable y and the independent variable x is known. However, in many practical situations like that of experimental data generated, the explicit relation between the dependent and independent variables is unknown
Title: Concise Physics BSc VI Semester Volume 8 (603)




9. Introduction to Finite Element Method(Finite Element Method) 
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Introduction, General Description of the Finite Element Method, List of Steps Involved in the Finite Element Method, Engineering Applications of Finite Element Method, Advantages of the Finite Element Method.
Title: Finite Element Method






11. Numerical Solution of System of Linear Equations(Mathematics) 
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This unit deals with the various direct methods of solving linear system of
simultaneous equations, the prominent methods being the Gauss elimination and the iterative procedures of GaussSeidels are explored.
Title: Math 3.5 Computer Programming




12. SECOND YEAR HANDBOOK (Mechanical Engineering) 
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The Hand Book provides you the detailed Syllabus and Exam Pattern of REVA University
Title: MECHANICAL ENGINEERINGHANDBOOK




13. Lagrange and Newton Interpolations and Finite Difference Operators(Mathematics) 
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There are two main uses of .interpolation or 'interpolating polynomials. The first use is in reconstructing the function f(x) when it is not given explicitly and only the value of f(x) and / or its certain order derivatives at it set of points, called nodes; tabular points or arguments are known. The second use is to replace the function f(x) by and interpolating polynomial P(x) so that many commo
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Title: Math 2.4 Numerical Analysis




14. Setting up of First Order Differential Equations and their Solutions(Mathematics) 
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Differential equations occur quite frequently in our daily life. The motion of an object can always be associated with a differential equation. The change in prices of commodities, the flow of fluids, the concentration of chemicals etc., often lead to differential equations. Such equations may depend on one or more independent variables. Further, it may include the derivatives of the first or high
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Title: Math 3.4 Mathematical Modeling




15. Mathematical Modeling of Some Fundamental Problems(Mathematics) 
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Mathematical Modeling in terms of differential equations arises when the situation modeled involves some continuous variables varying with respect to other continuous variables and we have reasonable hypothesis about the rate of change of dependent variables with respect to independent variables. Mathematical models in terms of ordinary differential equations will be studied in this unit and the u
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Title: Math 3.4 Mathematical Modeling




16. Difference Equations and Generating Functions(Mathematics) 
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After going through this unit we can define and construct generating functions for sequences arising in various types of combination problems. Also we use generating functions to find the number of integer solution to linear equations. We solve recurrence relation using generating functions.
Title: Math 1.4 Discrete Mathematics




17. Mathematical Modelling for Convection Diffusion and Reaction Processes(Mathematics) 
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After studying this unit, students will be able to analyse about convection diffusion processesBurger's equation which will cover Burger's equation and the plane wave solution, ColeHopf transformation and the exact solution of Burger's equation. They will also be able to explain asymptotic behavior of the exact solution of Burger's equation and Burger's initial and boundary value problem and exp
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Title: Math 3.4 Mathematical Modeling




18. Introduction to mathematical Modeling(Mathematics) 
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A mathematical model is a description of a system using mathematical concepts and language. The process of developing a mathematical model is termed mathematical modeling. Mathematical models are used not only in the natural sciences such as physics, biology, earth science, meteorology and engineering disciplines like computer science, artificial intelligence, but also in the social sciences Physi
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Title: Math 3.4 Mathematical Modeling




19. Situations giving rise to Partial Differential Equations(Mathematics) 
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A mass balance is an application of conservation of mass to the analysis of physical systems. By accounting for material entering and leaving a system, mass flows can be identified which might have been unknown or difficult to measure without this technique.
Title: Math 3.4 Mathematical Modeling




20. Field Extensions(Mathematics) 
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Given any algebraic structure such as group, ring or a vector space, we have considered subalgebraic structures such as subgroups, sub rings or a subspace. In a similar fashion we shall define subfield and an extension field of a field. In group theory it is customary to ask questions about the subgroups of a given group.
Title: Math 1.1 Algebra




21. Dynamic Analysis(Finite Element Method) 
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Introduction, Equation Of Motion, Orthogonality Of The Eigenvectors, Formulation Of Inertial Properties, Solution Techniques For Eigenproblems.
Title: Finite Element Method




22. Limitations of Mathematical Modeling(Mathematics) 
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A crucial part of the modeling process is the evaluation of whether or not a given mathematical model describes a system accurately. This question can be difficult to answer as it involves several different types of evaluation. In this regard we have discussed the limitations of modeling in following sections.
Title: Math 3.4 Mathematical Modeling




23. PredictorCorrector Methods and Stiff System(Mathematics) 
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We shall discuss the application of the explicit and implicit multistep methods for the solution of the initial value problems in this unit.
Title: Math 2.4 Numerical Analysis




24. Ordinary Differential Equations and Finite Difference Methods(Mathematics) 
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This unit explains Initial Value Problem and linear second order differential equations. It also explains nonlinear second order differential equations. and describes finite difference methods.
Title: Math 2.4 Numerical Analysis




25. Introduction of Scientific Research and Good Scientific Practices (GSP)(Clinical Nutrition and Dietetics) 
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The scientific enterprise is built on a foundation of trust. Society trusts that scientific research results are an honest and accurate reflection of a researcher's work. Researchers equally trust that their colleagues have gathered data carefully, have used appropriate analytic and statistical techniques, have reported their results accurately, and have treated the work of other researchers with
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Title: MSc.CND103 Research Methods and Biostatistics






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