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A radial basis function neural network (RBFNN) is developed and applied to analyze one-dimension periodic defected ground structure (1-D DGS).
Microstrip filter with defected ground structure: A close perspective · Artificial Neural Network Method for the Analysis of 1-D Defected Ground Structure.
A radial basis function neural network (RBFNN) is developed and applied to analyze one-dimension periodic defected ground structure (1-D DGS).
This paper presents a comprehensive review of the general architecture and principals of 1D CNNs along with their major engineering applications.
Feb 1, 2017 · A basic concept behind the DGS technology and several theoretical techniques for analysing the Defected Ground Structure are discussed. Several ...
Missing: Neural | Show results with:Neural
May 13, 2024 · This research aims to provide a comprehensive assessment of the applications of ANN, ML, DL, and EL in addressing forecasting within the field related to ...
This manuscript proposes a Prediction of Microstrip Antenna Dimension using Auto-Metric Graph Neural Network is optimized with Sheep Flock optimization ...
Mar 23, 2022 · The core idea is that first, (1) GD is applied to increase the convergence speed. (2) If the network is stuck in local minima, the capacity of ...
Missing: Defected | Show results with:Defected
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Oct 10, 2022 · In this paper, we develop a simpler ANN model by using structural learning with forgetting (SLF) as the algorithm for the training process.
Abstract—This paper presents the use of artificial neural network for the estimation of cut-off frequency in a design of. Low Pass filter (LPF) by varying ...
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