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210731s2021 xx o ||| 0 eng d |
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|a EBLCP
|b eng
|c EBLCP
|d EBLCP
|d LOA
|d OCLCF
|d OCLCQ
|d OCLCO
|d OCLCL
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|a 9781630817763
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|a 1630817767
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|a (OCoLC)1262374049
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|a Q325.5
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|a 006.31
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| 049 |
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|a UAMI
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| 100 |
1 |
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|a Martínez-Ramón, Manel.
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| 245 |
1 |
0 |
|a Machine Learning Applications in Electromagnetics and Antenna Array Processing
|h [electronic resource].
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| 260 |
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|a Norwood :
|b Artech House,
|c 2021.
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| 300 |
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|a 1 online resource (349 p.)
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| 500 |
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|a Description based upon print version of record.
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| 505 |
8 |
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|a 3.4 Kernel Framework for Estimating Signal Models -- 3.4.1 Primal Signal Models -- 3.4.2 RKHS Signal Models -- 3.4.3 Dual Signal Models -- References -- 4 The Basic Concepts of Deep Learning -- 4.1 Introduction -- 4.2 Feedforward Neural Networks -- 4.2.1 Structure of a Feedforward Neural Network -- 4.2.2 Training Criteria and Activation Functions -- 4.2.3 ReLU for Hidden Units -- 4.2.4 Training with the BP Algorithm -- 4.3 Manifold Learning and Embedding Spaces -- 4.3.1 Manifolds, Embeddings, and Algorithms -- 4.3.2 Autoencoders -- 4.3.3 Deep Belief Networks -- References -- 5 Deep Learning Structures -- 5.1 Introduction -- 5.2 Stacked Autoencoders -- 5.3 Convolutional Neural Networks -- 5.4 Recurrent Neural Networks -- 5.4.1 Basic Recurrent Neural Network -- 5.4.2 Training a Recurrent Neural Network -- 5.4.3 Long Short-Term Memory Network -- 5.5 Variational Autoencoders -- References -- 6 Direction of Arrival Estimation -- 6.1 Introduction -- 6.2 Fundamentals of DOA Estimation -- 6.3 Conventional DOA Estimation -- 6.3.1 Subspace Methods -- 6.3.2 Rotational Invariance Technique -- 6.4 Statistical Learning Methods -- 6.4.1 Steering Field Sampling -- 6.4.2 Support Vector Machine MuSiC -- 6.5 Neural Networks for Direction of Arrival -- 6.5.1 Feature Extraction -- 6.5.2 Backpropagation Neural Network -- 6.5.3 Forward-Propagation Neural Network -- 6.5.4 Autoencoder Framework for DOA Estimation with Array Imperfections -- 6.5.5 Deep Learning for DOA Estimation with Random Arrays -- References -- 7 Beamforming -- 7.1 Introduction -- 7.2 Fundamentals of Beamforming -- 7.2.1 Analog Beamforming -- 7.2.2 Digital Beamforming/Precoding -- 7.2.3 Hybrid Beamforming -- 7.3 Conventional Beamforming -- 7.3.1 Beamforming with Spatial Reference -- 7.3.2 Beamforming with Temporal Reference -- 7.4 Support Vector Machine Beamformer -- 7.5 Beamforming with Kernels.
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| 505 |
8 |
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|a 7.5.1 Kernel Array Processors with Temporal Reference -- 7.5.2 Kernel Array Processor with Spatial Reference -- 7.6 RBF NN Beamformer -- 7.7 Hybrid Beamforming with Q-Learning -- References -- 8 Computational Electromagnetics -- 8.1 Introduction -- 8.2 Finite-Difference Time Domain -- 8.2.1 Deep Learning Approach -- 8.3 Finite-Difference Frequency Domain -- 8.3.1 Deep Learning Approach -- 8.4 Finite Element Method -- 8.4.1 Deep Learning Approach -- 8.5 Inverse Scattering -- 8.5.1 Nonlinear Electromagnetic Inverse Scattering Using DeepNIS -- References -- 9 Reconfigurable Antennas and Cognitive Radio -- 9.1 Introduction -- 9.2 Basic Cognitive Radio Architecture -- 9.3 Reconfiguration Mechanisms in Reconfigurable Antennas -- 9.4 Examples -- 9.4.1 Reconfigurable Fractal Antennas -- 9.4.2 Pattern Reconfigurable Microstrip Antenna -- 9.4.3 Star Reconfigurable Antenna -- 9.4.4 Reconfigurable Wideband Antenna -- 9.4.5 Frequency Reconfigurable Antenna -- 9.5 Machine Learning Implementation on Hardware -- 9.6 Conclusion -- References -- About the Authors -- Index.
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| 590 |
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|a ProQuest Ebook Central
|b Ebook Central Academic Complete
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| 650 |
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0 |
|a Machine learning.
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| 650 |
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6 |
|a Apprentissage automatique.
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| 650 |
|
7 |
|a Machine learning
|2 fast
|
| 700 |
1 |
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|a Gupta, Arjun.
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| 700 |
1 |
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|a Rojo-Álvarez, José Luis.
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| 758 |
|
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|i has work:
|a Machine learning applications in electromagnetics and antenna array processing (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCGHQBkrwCVfKGDJxcRBfpX
|4 https://id.oclc.org/worldcat/ontology/hasWork
|
| 776 |
0 |
8 |
|i Print version:
|a Martínez-Ramón, Manel
|t Machine Learning Applications in Electromagnetics and Antenna Array Processing
|d Norwood : Artech House,c2021
|z 9781630817756
|
| 856 |
4 |
0 |
|u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=6683918
|z Texto completo
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| 938 |
|
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|a ProQuest Ebook Central
|b EBLB
|n EBL6683918
|
| 994 |
|
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|a 92
|b IZTAP
|
