Learning-by-examples techniques as applied to electromagnetics
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Summary
This paper aims to present an overview of the state-of-the-art and recently developed LBE-based strategies as applied to the solution of engineering problems in the field of Electromagnetics.
- Type
- article
- Published
- 2018-03-04
- Cited by
- 151
- References
- 127
- OpenAlex
- https://openalex.org/W2769250359
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:115579229
Keywords
Electromagnetics, Computer science, A priori and a posteriori, Computational electromagnetics, Field (mathematics)
References
- Introduction to Inverse Problems in Imaging
- Passive imaging strategies for real-time wireless localization of non-cooperative targets in security applications
- Reactive Search and Intelligent Optimization
- Automatic Classification of Ground-Penetrating-Radar Signals for Railway-Ballast Assessment
- Engineering Design via Surrogate Modelling - A Practical Guide
- Applications of Neural Networks in Electromagnetics
- A Comparative Study of NN and SVM-Based Electromagnetic Inverse Scattering Approaches to On-Line Detection of Buried Objects
- Soil Moisture Retrieval Using Neural Networks: Application to SMOS
- Complex radome design through the Systems-by-Design approach
- A learning-by-examples approach for non-destructive localization and characterization of defects through eddy current measurements
- An Efficient Method for Antenna Design Optimization Based on Evolutionary Computation and Machine Learning Techniques
- Time Delay and Permittivity Estimation by Ground-Penetrating Radar With Support Vector Regression
- The Elements of Statistical Learning: Data Mining, Inference, and Prediction
- A Support Vector Machine MUSIC Algorithm
- A SVM-based approach to microwave breast cancer detection
- Multi-Objective Design of Antennas Using Variable-Fidelity Simulations and Surrogate Models
- System-by-design: A new paradigm for handling design complexity
- Defect Characterization With Eddy Current Testing Using Nonlinear-Regression Feature Extraction and Artificial Neural Networks
- Computation of the field radiated by a FM transmitter by means of ordinary kriging
- Signal‐noise support vector model of a microwave transistor
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- Robust real‐time inversion of electrical impedance tomography data for human lung ventilation monitoring
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- Human chest imaging by real-time processing of electrical impedance data tomography
- Antenna array synthesis based on pre‐process coding neural network
- Advanced statistical learning method for multi-physics NDT-NDE
- Instantaneous brain stroke classification and localization from real scattering data
- Real-Time Electrical Impedance Tomography of the Human Chest by Means of a Learning-by-Examples Method
- Looking for the Optimal Trade-Off between Computational Costs and Reliability in Synthesizing High-Complexity Electromagnetic Systems - the Case of Satellite Communications Antenna Design
- Robust BCS-based Direction-of-Arrival and Bandwidth Estimation of Unknown Signals for Cognitive Radar
- Dealing with Complexity in Electromagnetics through the System-by-Design Paradigm - New Strategies and Applications to the Design of Airborne Radomes
- PSO-Driven Synthesis of Realistic Time Modulated Arrays with Optimal Instantaneous Directivity through a System-By-Design Implementation
- An Innovative Learning-by-Examples Method for Real-Time Electrical Impedance Tomography of the Human Chest
- Performance Analysis and Dynamic Evolution of Deep Convolutional Neural Network for Electromagnetic Inverse Scattering
- An adaptive sampling strategy for quasi real time crack characterization on eddy current testing signals
- A nonlinear Kernel-based adaptive learning-by-examples method for robust NDT/NDE of conductive tubes
- System‐by‐design method for efficient linear array miniaturisation through low‐complexity isotropic lenses
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