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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.
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
Anonymous Functions: The anonymous function is a very easy, one-line function. The benefit of an anonymous function is that it does not have to be stored in an M-file. This ca
Patch function - graphics objects: The patch function is used to generate a patch graphics object, which is made from 2-dimensional polygons. The patch is defined by its verti
. Generate the following signal, x(n)=1+cos((25*pi*n)/100),0 Compute the DTFT of x[n] for w=0:0.01:2*pi Plot the Real part, imaginary part, the amplitude and phas
Illustration of Sound files: For illustration, the following script generates a subplot which shows the signals from chirp and from train, which is as shown in figure:
Appending variables to the Mat-File: Appending to the file adds to what has been saved in a file, and is accomplished by using the -append option. For illustration, supposing
Displaying expressions: The good-looking function will show such expressions by using exponents; for illustration, >> b = sym('x^2') b = x^2 >> pretty(b)
Gauss Elimination: The Gauss elimination technique consists of: Generating the augmented matrix [A b] Applying EROs to augmented matrix to obtain an upper trian
Implementation of binary search: The binary search can be implemented as a recursive function. The recursive function below also implements this binary search algorithm. It re
How can I use the weighted moving average formula in matlab to smooth a column data of 404 values?
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