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Numerical analysis is the study of algorithms that use numerical approximation (as opposed to symbolic manipulations) for the problems of mathematical analysis (as distinguished from discrete mathematics ). It is the study of numerical methods that attempt to find approximate solutions of problems rather than the exact ones.
Learn the basic techniques for the efficient numerical solution of problems in science and engineering. This course covers root finding, interpolation, approximation, integration, differential equations, and linear algebra methods.
In practice, we use a biased exponent to allow negative exponents. In single-precision, a stored exponent e represents a true exponent e 127. This representation is called \excess-127" (single precision) or \excess-1023" (double precision).
Find the PDF files of the lecture notes for Introduction to Numerical Analysis, a mathematics course offered by MIT OpenCourseWare. The notes cover topics such as series, integrals, interpolation, nonlinear equations, differential equations, Fourier analysis and spectral methods.
1.1 What is Numerical Analysis? . . . . . . . . . . . . . . . . . .3 1.2 An Illustrative Example . . . . . . . . . . . . . . . . . . . . .3 1.2.1 An Approximation Principle . . . . . . . . . . . . . . .4
Learn what numerical analysis is, how it gives approximate answers using simple calculations, and what methods and errors are involved. Explore examples of finding roots, integrals, and modeling real-world phenomena with numerical analysis.
Learn how to handle functions, derivatives, integrals, and differential equations as strings of numbers in the computer. Topics include series expansions, interpolation, ODE, Fourier transform, least-squares, and spectral methods.
