MHB Can This Forgotten Formula Simplify the Laplace Transform of \(y(t)^3\)?

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The discussion centers on computing the Laplace transform of \(y(t)^3\) using a lesser-known formula, which simplifies the process if the Laplace transform of \(y(t)\) is already known. A user on mathhelpforum.com inquired about this computation, and it was noted that direct application of the Laplace transform definition would typically be necessary without prior knowledge of \(y(t)\). However, the "forgotten formula" referenced is found in the textbook by N. Balabanian and T.A. Bickart, which provides a method for transforming the product of two functions. This formula allows for a more efficient calculation of the Laplace transform of \(y(t)^3\). The discussion highlights the value of revisiting established mathematical resources for solving complex problems.
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As You can see in…

laplace transform of y(t) whole power 3

… on mathhelpforum.com a ‘newbie’ user asked to know how compute, given an $y(t)$ the L-Transform $\mathcal {L} \{y^{3}(t)\}$. At first, without any knowledege of y(t), it seems that no other chance exists apart the direct definition of L-Transform. Surprisinghly enough, if the L-Transform $\mathcal{L} \{y(t)\}$ is known, a 'magic and forgotten formula' conducts to the result. The formula can be found in Appendix two of the electrical engineering textbook 'N. Balabanian, T.A. Bickart, Electrical Network Theory, 1969, Wiley & Sons, New York' where You can read... Let be $f_{1}(t)$ and $f_2(t)$ two functions and their L-Transform $F_{1}(s)= \mathcal{L} \{f_{1}(t)\}$ and $F_{2}(s)= \mathcal{L} \{f_{2}(t)\}$ converge for $\text{Re} (s)> \sigma_{1}$ and $\text{Re} (s)> \sigma_{2}$ respectively. In this case is... $\displaystyle \mathcal{L} \{f_{1}(t)\ f_{2}(t)\} = \frac{1}{2\ \pi\ i}\ \int_{c - i \infty}^{c + i \infty} F_{1}(z)\ F_{2} (s-z)\ dz$ (1)... where $\sigma_{1} < c < \sigma - \sigma_{2}\ , \sigma > \sigma_{1} + \sigma_{2}$ ...

As in the famous James Bond's film : never say never again!...

Kind regards

$\chi$ $\sigma$
 
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