Introduction to Application of ANN on Microwave Engineering:

ANN is an extensively used for pattern recognition, speech recognition, and for simulation of complex process. It is being used in different application of microwave engineering.  They are neuroscience inspired for computational tools. It is used when problems are poorly understood, difficult to carry out operation, or to solve complex problem, particular with non-linear systems.

Neural model consist of three layers: output lines, hidden layer, input lines.

Smart antenna modeling: it is a system that is array combined with signals both in air and space. These systems use technique to improve the quality of received signal ad increase the capacity of signal.

There are three main steps; first step is initialization and selection. In these step neurons sensors are distributed for supplying areas. Then random neuron is selected and supplied. If neurons are not supplied then power in increased and if they are supplied then power will decrease. Second step is adaptation: it receive energy from current system, check its transmitting station. Now after their displacement their current position is right then they are forwarded. Third step is optimization; energy if current system is checked, then it is matched with 0, if it less than 0 they are carried forward otherwise they are send to select a random number, then we find the probability of that number, check it again with number, if that condition is true then we got reduction in temperature.

Future application: they will be used in fractals antennas/arrays and for increasing the efficiency for solving the various algorithms of antenna like MoM, FDTD, and FEM etc.

Conclusion: they minimize the human effort for solving complex problem, and the use of ANN will be major factor for solving huge amount of data, where decision making is critical and their environment is complex.

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