  There are important algorithms built upon a mixture of basic techniques
described; for example, the Fast Fourier Transform (FFT) employs both
Divide-and-Conquer and Transform-and-Conquer techniques. In this article, the
evolution of a quantum algorithm (QA) is examined from an information theory
viewpoint. The complex vector entering the quantum algorithmic gate - QAG is
considered as an information source both from the classical and the quantum
level. The analysis of the classical and quantum information flow in
Deutsch-Jozsa, Shor and Grover algorithms is used. It is shown that QAG, based
on superposition of states, quantum entanglement and interference, when acting
on the input vector, stores information into the system state, minimizing the
gap between classical Shannon entropy and quantum von Neumann entropy.
Minimizing of the gap between Shannon and von Neumann entropies is considered
as a termination criterion of QA computational intelligence measure.
