Root finding methods for Polynomials.

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Root finding methods for polynomials can effectively identify both real and complex roots, with techniques like Bairstow's method being particularly useful. This method allows for the determination of all roots, including those with larger and smaller real parts. MATLAB offers a numerical approach that converts the problem into an eigenvalue problem, ensuring fast convergence and accuracy when eigenvalues are well separated. A good starting value is essential for successful implementation of these algorithms. Overall, various methods exist to accurately find polynomial roots, including complex ones.
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Hi , is there a method to obtain the roots of Polynomials:

P(x)=a_{0}+a_{1}x+a{2}x^{2}+...+a_{n}x^{n}

i know there are , but my problem is this if we knew that are complex roots of the form z=a+ib , would be a method to obtain the complex root with BIGGER and SMALLER real part ?? , i mean for example if a POlynomial has complex root:

1+3i 1-3i 0.6+8i 0.6-8i 0.01+34i 0.01-34i ...

my question is if we could use a root finding algorithm to check that the bigger part of the roots is '1'
 
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I'm not sure what you mean. Matlab has a good method for finding the roots numerically. It transfers the roots of polynomial to an eigvenvalue problem. It converges quite fast and will give you all the roots. It is quite accurate if the eignvalues are well separated.
 
One method to find all roots is the one of Bairstow. This gives you not only the real, but also the complex ones. Look here for some info, and google a bit to find some more:

http://en.wikipedia.org/wiki/Bairstow's_method

The implementation is not that difficult, I've done it and it works fine. The only thing to take care of is a good starting value, but even that can be solved.
 
Thread 'Erroneously  finding discrepancy in transpose rule'
Obviously, there is something elementary I am missing here. To form the transpose of a matrix, one exchanges rows and columns, so the transpose of a scalar, considered as (or isomorphic to) a one-entry matrix, should stay the same, including if the scalar is a complex number. On the other hand, in the isomorphism between the complex plane and the real plane, a complex number a+bi corresponds to a matrix in the real plane; taking the transpose we get which then corresponds to a-bi...

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