This study performed modeling of the scattering (S) and noise (N) parameters of the ATF53189 using the General Regression Neural Network (GRNN) and Multi Layer Perceptron Neural Network (MLPNN) methods based on Artificial Neural Network (ANN). For modeling the linear behavior of the transistor, the optimum design parameters of the GRNN and the MLPNN methods were determined using four different optimization algorithms. These are whale optimization algorithm (WOA), artificial bee colony (ABC), particle swarm optimization (PSO) and ant lion optimizer (ALO) algorithms. With the help of these algorithms, the sigma parameter of the GRNN and the number of hidden layers, numbers of neurons in the hidden layers and the activation functions of the hidden layers of the MLPNN were optimized. This way, the best models required for prediction of the S and N parameters of the ATF53189 were obtained. Different models that provided each of the angles and magnitudes of the S11, S21, S12, S22 parameters and the Fmin, Γmin, Γopt magnitude, Γopt angle and Rn noise parameters as the output were created. The experimental results showed that the GRNN method should be used in linear behavior modeling of S parameters of the ATF53189 and the MLPNN method should be used in linear behavior modeling of N parameters of the ATF53189. It is understood that the best algorithm for optimizing the design parameters of the GRNN and the MLPNN methods is the PSO. As a result, the modeling of the S and N parameters of the ATF53189 transistor was successfully carried out with the methods used in this study.
Sistem yazılım alt yapısını oluşturan mikrodenetleyici ile sisteme adaptiflik özelliği kazandırılmıştır. Çalışmada GY'ye adaptiflik özelliği kazandıran tüm sistem elemanları ayrı ayrı tasarlanmıştır. Sistem yazılımının mikrodenetleyici ile yapılması maliyeti azaltmıştır. GY'ye adaptiflik özelliği kazandırmaktaki amaç, GY doğrusallık ve verim performansını kararlı hale getirmektir. Bu sebeple, çalışmada birisi 5 dB diğeri 10 dB olmak üzere farklı iki kazanç (G) değeri seçilmiştir. GY girişine gelmesi olası tüm Pgiriş değerleri için, GY G'sini seçilen değerlerde sabit tutacak VDC gerilimleri tasarlanan adaptif sistem tarafından üretilmektedir. GY G'sinin sabit tutulmasındaki amaç, GY'nin sabit VDC beslemesi ile oluşabilecek G bozulmasını kompanze etmek ve GY için doğrusallık kriteri olan P1dB noktasını ötelemektir. Adaptif sistem ile GY için G kontrolü ile beraber verim kontrolü de yapılmakta ve GY veriminin belirli bir değerin altına düşmesi önlenmektedir.
This study investigates changes of S-parameters (S21, S11, S22, S12) of a SBB5089Z power amplifier module in relation to changing DC conditions. Behaviour of those linear performance parameters (S21, S11, S22, S12) was examined graphically. S-parameters of SBB5089Z were analysed covering the 5.8 GHz WiMAX frequency from 5.7 GHz to 5.9 GHz with 200 MHz bandwidth. DC conditions were controlled using a microcontroller, an R/2R Digital Analogue Converter (DAC) ladder circuit and a voltage follower with LM324. The R/2R ladder circuit and voltage follower with LM324 have been integrated with the microcontroller. Also ACS712 current sensor and ADS1115 16-bit Analog Digital Convertor (ADC) are integrated to the microcontroller. PA’s current was read with microcontroller.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.