Hi, I put a polynom ( x^2+x-1) in a form of a vector :
[1 1 -1].I don't know how to derivate this vector and how to evaluate it.
Thanks, Thierry.

 Accepted Answer

Claudio Contrada
Claudio Contrada on 1 Feb 2023
hi, use the polyder() function, which returns the coefficients of the derivate as a vector. so if p=[1 1 -1], we have p1=polyder(p). this assigns to p1 the arrray [2 1].

1 Comment

Although it is not completely clear from the original question, I believe that this is the correct answer.

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More Answers (3)

Not sure how those 3 numbers came from that equation, but anyway....The derivative is the slope. You have two line segments, from 1 to 1 and from 1 to -1. So the slope of the first line segment is 0 and the slope of the second line segment is -2. You can get this from
slopes = diff(yourVector);
If you want to evaluate your polynomial and do a numerical derivative, use the polyval function to evaluate it, then the gradient function to take the derivative:
h = 0.1; % Spacing Constant
x = -5:h:5; % Independent Variable Vector
y = polyval([1 1 -1], x); % Evaluate Polynomial
dydx = gradient(y, h); % Take Numerical Derivative At Each Value Of ‘x’
Note that unlike diff, the gradient function will produce a vector the same length as the original data vector.

3 Comments

Why use the crude 'gradient' function when the precise derivatives for polynomials can be determined as given by Mohammad Abouali?
Because I don’t know what the problem actually is.
Is Thierry supposed to evaluate the polynomial and then take the numerical derivative, or evaluate the polynomial and its analytic derivative at the same values of x?
I’m offering the best numerical derivative function as an option.
I agree with Star. The language in the question is so imprecise, it's impossible to determine if the [1 1 -1] vector is the x input vector or the polynomial y output vector. So I also gave a numerical answer. If the x location(s) where the derivative is known for certain, then you could just use calculus to determine the slope as 2*x+1 and plug in the x where you want the slope computed at.

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additionally to the above answers, the simplest way to evaluate the polynomial is via anonymous function :
f=@(x) x.^2+x-1
x=0:0.1:10;
Generally, coefficients vector is used to find the roots. concerning the derivation, gradient is more efficient than diff, when you have the sample rate :
df=gradient(f(x),0.1);
plot(x,f(x),x,df,'r')

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