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This paper presents a DNA based classification technique. It exploits the properties of the DNA as a quaternary logic with the advantages of better storage, better accuracy, and shorter time compared to binary logic. Several examples are employed to demonstrate using the DNA as a new classification method for differentiation between closely related objects such as boys and girls also we used neural network to demonstrate better accuracy and predict some objects for example boys. In addition the explanation of DNA computing, Boolean Circuit using DNA, Molecular Beacons, also DNA logic gates and some applications using DNA computing. Several programming tools are used to illustrate that using the MATLAB program. General TermsDNA computing.

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A noise model for heterojunction transistors using a new technique for prediction was introduced using a neural network model, and was applied to get higher accuracy for transistor noise parameters. The new model is employed in designing of a wideband Low-Noise Amplifier (LNA), which resulted higher accuracy for the four noise parameters required, using only one neural network for simulation of noise figure parameters. The accuracy of this model has been demonstrated by coordinating anticipated and estimated values of heterojunction transistors for a specific data set of noise parameters at various frequencies, temperatures and bias points. DNA computing was used to design a Low-Noise Amplifier (LNA). The DNA computing method demonstrates good and very accurate results and also shows a very high accurate results in prediction of the noise parameters by using it as FFNN to determine a threshold level value, which consequently increased the gain leading to higher bandwidth. Comparison of the new method (DNANN) to other classical optimization techniques shows that the DNA computing method results in optimized noise parameters, which consequently leads to higher LNA gain which consequently leads to improved bandwidth. Copyright © 2017 Penerbit Akademia Baru - All rights reserved.