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not be found analytically. MATLAB has a built-in command that finds all the
                             roots (real and complex) for any polynomial equation. As previously noted,
                             the MATLAB command for finding the polynomial roots is roots:
                                r=roots(p)

                             In interpreting the results from this command, recall the Fundamental Theo-
                             rem of Algebra, which states the root properties of a polynomial of degree n
                             with real coefficients:

                                1. The n  polynomial admits n complex roots.
                                        th
                                2. Complex roots come in conjugate pairs. [If you are not familiar
                                   with complex numbers and with the term complex conjugate (the
                                   latter term should pique your curiosity), be a little patient. Help is
                                   on the way; Chapter 6 covers the topic of complex numbers].

                              Inversely, knowing the roots, we can reassemble the polynomial. The com-
                             mand is poly.

                                poly(r)



                             In-Class Exercise

                             Pb. 5.14 Find the roots of the polynomial p = [13210    3], and com-
                             pute their sum and product.
                             Pb. 5.15 Consider the two polynomials:

                                          p  = [132103]and p  = [3            2  1]
                                           1
                                                                       2
                             Find the value(s) of x at which the curves representing these polynomials
                             would intersect.
                             Pb. 5.16 Find the constants A, B, C, D, and a, b, c, d that permits the follow-
                             ing expansion in partial fractions:

                                               1      =   A   +   B  +   C   +  D
                                         x − 25x +  144  ( x −  a)  ( xb− )  ( xc− )  ( xd− )
                                          4
                                                2






                             5.3  Optimization Methods

                             Many design problems call for the maximization or minimization (optimiza-
                             tion) of a particular function belonging to a particular domain. (Recall the


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