abstract = "Analog electrical circuits that perform mathematical
functions (e.g., cube root, square) are called
computational circuits. Computational circuits are of
special practical importance when the small number of
required mathematical functions does not warrant
converting an analog signal into a digital signal,
performing the mathematical function in the digital
domain, and then converting the result back to the
analog domain. The design of computational circuits is
difficult even for mundane mathematical functions and
often relies on the clever exploitation of some aspect
of the underlying device physics of the components.
Moreover, implementation of each different mathematical
function typically requires an entirely different
clever insight. This paper demonstrates that
computational circuits can be designed without such
problem-specific insights using a single uniform
approach involving genetic programming. Both the
circuit topology and the sizing of all circuit
components are created by genetic programming. This
uniform approach to the automated synthesis of
computational circuits is illustrated by evolving
circuits that perform the cube root function (for which
no circuit was found in the published literature) as
well as for the square root, square, and cube
functions.",