This work presents methodology for an automated design of analog circuits using global
Artificial Neural Network (ANN) for an optimised dataset. The optimised dataset is generated …

In the proposed paper, an artificial neural network (ANN) algorithm is applied to predict the
electronic circuit outputs of voltage signals in Industry 4.0/5.0 scenarios. This approach is …

The aim of the paper is to present a two-step method for facilitating the design of analog
amplifiers taking into account the bottom–top approach and utilizing machine learning …

Linear Regression (LR), as one of the essential Machine Learning (ML) models, incurs
massive data crunching during the training phase based on many data points. Considering …

We present an application of machine learning to automated robust optimization of
electronic circuit design that combines artificial neural networks and global optimization. A …

Learning are being discussed in this paper. Moreover, major parameters like power
efficiency, delay and accuracy is being taken into consideration for verifying the result. The …

The design of analog circuits is a complex and repetitive process aimed at finding the best
design variant. It is characterized by uncertainty and multivariate approaches. The designer …

Deep learning with neural network could learn many features and skills to perform various
tasks, including digital circuit design. Previous exploration proved that artificial neural …

The robot dynamic model is often rarely known due to various uncertainties such as
parametric uncertainties or modeling errors existing in complex environments. It is a key …

Bu çalışmada ikinci kuşak akım taşıyıcı (CCII) için yapay sinir ağları ile performans
parametreleri tahmin edilmiştir. Öncelikle seçilen CCII'nin CMOS gerçeklemesindeki …