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Interpolation and extrapolation:
In most cases, it is desired to estimate values other than at the sampled data points. For illustration, we may want to estimate what the temperature was at 2:30 p.m., or at 1 p.m. Interpolation is estimating the values in between recorded data points. The Extrapolation is estimating outside the bounds of the recorded data. The one way to do this is to fit a curve to the data, and use this for the estimations. The Curve fitting is finding the curve which "best fits" the data.
The Simple curves are polynomials of various degrees. Therefore, curve fitting includes finding the best polynomials to fit the data-for illustration, for a quadratic polynomial in the form ax2 + bx + c, it means finding the values of a, b, and c which results the best fit. Finding the best straight line which goes through data would mean finding the values of a and b in the equation ax + b.
Text graphic function - Graphics objects: The text graphic function permits text to be printed in a Figure Window, involving special characters which are printed by using \spe
Technique is to create one element - vector: Technique is to create one element with the values from one structure, and use repmat to replicate it to the preferred size. Then,
Forward substitution: The Forward substitution (done methodically by first getting a 0 in the a 21 place, and then a 31 , and lastly a 32 ): For the Gauss technique,
num2str function: The num2str function, that converts real numbers, can be called in many ways. If only the real number is passed to the num2str function, it will generate a s
A matlab function to calculate filter order
Illustration sorting vectors of structures: This function sorts the structures depend only on the price field. A more common function is shown next, that receives a string whi
Vectors of Structures: In numerous applications, involving database applications, information generally would be stored in the vector of structures, instead of in individual s
Modular programs: In a modular program, the answer is broken down into modules, and each is executed as a function. The script is usually known as the main program. In orde
7.13
Algorithm for the function explaine: The algorithm for the function explaine is as shown: Print a description of e, the exp function, and how to find the approximate va
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