Sparse Matrix See help sparfun for detail Curve Fitting Polynomial curve fitting a=polyfit(x,y,n) do a least-square fit with polynomial of degree n. x and y are data vectors, and a is coefficients of the polynomial, a = [an, an-1, …, a1, a0] Curve Fitting y = polyval(a, x) compute the value of polynomial at value x y = a(1) xn + a(2) xn-1 + …
  • Apr 01, 2019 · Keep in mind that this is a simple example, and using the break MATLAB command here is really not recommended because you could just write this instead: for i = 1 : 51 end Using break comes in handy when you have nested for loops (i.e. a for loop within a for loop) because you can exit a loop based on a condition that is common to both loops.

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    "Polyfit" is a MATLAB function that computes a least squares polynomial for a given set of data. Polyfit actually generates the coefficients of the polynomial (which can be used to simulate a curve to fit the data) according to the degree specified. "Polyval" evaluates a polynomial for a given set of x values.

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    polyfit function in MATLAB [p = polyfit(x,y,n) returns the coefficients for a polynomial p(x) of degree n that is a best fit (in a least-squares sense) for the data in y. The coefficients in p are in descending powers, and the length of p is n+1 i.e. the first element of p will be coefficient corresponding to x^n , next coefficient of p will be ...

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