Langrage`s Interpolating Formula Derivation

Here we are interpolating a polynomial y = f(x). Where (x0,y0), (x1,y2), (x3,y3),……. (xn,yn) are n+1 calculated point. Let their points are exist
Xi= x0+ih where i =1, 2, 3….n
y = f(x) = a0(x-x1)(x-x2)(x-x3)……(x-xn)

Lagrange Interpolation Formula in Numerical Analysis/Techniques

Lagrange’s interpolation is an nth-degree polynomial approximation to f(x). we are discourse about the Lagrange interpolation and its formula. By using this formula we find the largest polynomial.

Secant Method in Numerical Analysis/Techniques

This method is quite similar to the Regula-falsi method except for the condition f(x1)f(x2)<0 In numerical analysis, the secant method is a root-finding procedure that uses a succession of roots of secant lines to better approximate the root of a function f.

 Newton’s Raphson Method

Newton’s method is also known as the Newton–Raphson method, named after Isaac Newton and Joseph Raphson, it is a root-finding algorithm which produces better approximations to the roots of a real-valued function.

What is Floating-Point Representation?

Introduction To Floating-Point Representation – Floating  Point Representation is the scientific notation of binary numbers. Floating  Point Representation is used for high-range values. It divides the number into three parts. The left-hand side represents a signed number and the right-hand side represents an exponent and the middle fixed point is called Mantissa.

Introduction to Numerical Techniques/ Analysis

Introduction to Numerical Techniques/ Analysis – Numerical techniques are the study of algorithms that are used for numerical approximation for the problems of mathematical analysis. A numerical method is complete and defines a set of methods for the solution of a problem, together with measurable error estimates. The study and implementation of such methods is the field of numerical analysis.