Affiliations: UAB, Department of Electrical and Computer
Engineering, Birmingham AL Erciyes University, Department of Computer
Engineering, Turkey | Erciyes University, Kayseri Vocational College,
Turkey
Abstract: The world, we live and will live in the future, is Analog.
Everything we can see, hear and perceive in life is Analog, from voice, music
and seismic activity to visual perception, voice recognition and energy
delivery. 20th Century scientists are still trying to understand and formulate
world events. For this aim they have produced a system, which is different
human machine language, name is Digital Systems. Digital Systems is only human
known and used systems. If anything in the world is wanted to be done in
digital language, firstly it has to be converted to digital language. After
digital conversion if you find any results, you have to re convert results into
Analog again, which is necessary for the real world, because world is
absolutely Analog. Sometimes this method brings us solutions, but the 20th
century designer scientists have reached some limits about creating answers in
hard, long ways. Therefore it is impossible to fathom engineering real-life
solutions without the help and support of high-performance Analog Electronics.
If we have a universal solution, Analog, in our hands why do we prefer to use
Digital Systems, Digital Application Specific Integrated Circuit (ASIC)
systems? The only answer must be "we cannot know or understand all details in
Analog Channel". At this point, this work is all about understanding and
rebuilding fundamentals of Analog Channels for Electronic Systems. This is one
of the most important engineering problems of our century. As a result, the aim
of selecting this work is recreating models and autonomous real world testing
system for new Analog Models, instead of Digital System Models. Selected
solution method is development of the MPI parallel computing architecture,
based on Artificial Intelligence Algorithms. In this proposed model, we
introduce an approach to develop a Message Passing Interface (MPI) Parallel
Computing Architecture using Genetic Algorithms (GA). We validate our approach
by applying the technique Analog Circuit Design technique.
