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To find all rational roots of a polynomial equation, you can use the Rational Root Theorem. This theorem states that any rational root of a polynomial equation in the form of (anxn an-1xn-1 ... a1x a0 0) must be a factor of the constant term (a0) divided by a factor of the leading coefficient (an). By testing these possible rational roots using synthetic division or polynomial long division, you can determine which ones are actual roots of the equation.
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How can MATLAB be used to find the roots of a given equation?
MATLAB can be used to find the roots of a given equation by using the built-in functions like "roots" or "fzero". These functions can solve equations numerically and provide the values of the roots. By inputting the equation into MATLAB and using these functions, the roots can be easily calculated and displayed.
How do you find the roots of an equation?
for an 2nd order the roots are : [-b+-sqrt(b^2-4ac)]/2a
How to find the roots of a function in MATLAB?
To find the roots of a function in MATLAB, you can use the "roots" function for polynomials or the "fzero" function for general functions. The "roots" function calculates the roots of a polynomial, while the "fzero" function finds the root of a general function by iteratively narrowing down the root within a specified interval.
Is the Ford-Fulkerson algorithm guaranteed to find the maximum flow in polynomial time?
No, the Ford-Fulkerson algorithm is not guaranteed to find the maximum flow in polynomial time.
What makes a problem pspace-hard and how does it impact the complexity of solving it?
A problem is considered PSPACE-hard if it is at least as hard as the hardest problems in PSPACE, a complexity class of problems that can be solved using polynomial space on a deterministic Turing machine. This means that solving a PSPACE-hard problem requires a significant amount of memory and computational resources. The impact of a problem being PSPACE-hard is that it indicates the problem is very difficult to solve efficiently, and may require exponential time and space complexity to find a solution.
