Error Analysis and Interpolation

Related lectures (28)

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Covers data manipulation and exploration using Python with a focus on visualization techniques.

Covers numerical integration methods, focusing on trapezoidal rules, degree of exactness, and error analysis.

Covers the least squares method for approximating data and handling errors.

Introduces Lagrange interpolation for approximating data points with polynomials, discussing challenges and techniques for accurate interpolation.

Explores splines, emphasizing the least-squares method for interpolating splines and demonstrating its application using MATLAB.

Explores trigonometric interpolation for approximating periodic functions and signals using equally spaced nodes.

Explores Gauss-Legendre quadrature formulas using Legendre polynomials for accurate function approximation.

Explores interpolation of regular functions, error analysis, convergence, and Chebyshev polynomials.

Introduces Reed Solomon Codes, their applications, polynomial definitions, interpolation, roots, and the Fundamental Theorem of Algebra.

Explores Lagrange interpolation, emphasizing uniqueness and simplicity in reconstructing functions from limited values.