home libri books Fumetti ebook dvd top ten sconti 0 Carrello


Torna Indietro
ARGOMENTO:  BOOKS > SCIENZA E TECNICA

jiao licheng; shang ronghua; liu fang; zhang weitong - brain and nature-inspired learning, computation and recognition

Brain and Nature-Inspired Learning, Computation and Recognition

; ; ;




Disponibilità: Normalmente disponibile in 20 giorni
A causa di problematiche nell'approvvigionamento legate alla Brexit sono possibili ritardi nelle consegne.


PREZZO
254,98 €
NICEPRICE
242,23 €
SCONTO
5%



Questo prodotto usufruisce delle SPEDIZIONI GRATIS
selezionando l'opzione Corriere Veloce in fase di ordine.


Pagabile anche con 18App Bonus Cultura e Carta del Docente


Facebook Twitter Aggiungi commento


Spese Gratis

Dettagli

Genere:Libro
Lingua: Inglese
Editore:

Elsevier

Pubblicazione: 01/2020





Note Editore

Brain and Nature-Inspired Learning, Computation and Recognition presents a systematic analysis of neural networks, natural computing, machine learning and compression, algorithms and applications inspired by the brain and biological mechanisms found in nature. Sections cover new developments and main applications, algorithms and simulations. Developments in brain and nature-inspired learning have promoted interest in image processing, clustering problems, change detection, control theory and other disciplines. The book discusses the main problems and applications pertaining to bio-inspired computation and recognition, introducing algorithm implementation, model simulation, and practical application of parameter setting.

Readers will find solutions to problems in computation and recognition, particularly neural networks, natural computing, machine learning and compressed sensing. This volume offers a comprehensive and well-structured introduction to brain and nature-inspired learning, computation, and recognition.



  • Presents an invaluable systematic introduction to brain and nature-inspired learning, computation and recognition
  • Describes the biological mechanisms, mathematical analyses and scientific principles behind brain and nature-inspired learning, calculation and recognition
  • Systematically analyzes neural networks, natural computing, machine learning and compression, algorithms and applications inspired by the brain and biological mechanisms found in nature
  • Discusses the theory and application of algorithms and neural networks, natural computing, machine learning and compression perception




Sommario

1. Introduction
2. The models and structure of neural network
3. Theoretical Basis of Natural Computation
4. Theoretical basis of machine learning
5. Theoretical basis of compressive sensing
6. SAR image
7. POLSAR Image Classification
8. Hyperspectral Image
9. Multiobjective Evolutionary Algorithm (MOEA) based Sparse Clustering
10. MOEA Based Community Detection
11. Evolutionary Computation Based Multiobjective Capacitated Arc Routing Optimizations
12. Multiobjective Optimization Algorithm Based Image Segmentation
13. Graph regularized Feature Selection based on spectral learning and subspace learning
14. Semi-supervised learning based on mixed knowledge information and nuclear norm regularization
15. Fast clustering methods based on learning spectral embedding
16. Fast clustering methods based on affinity propagation and density-weighted
17. SAR image processing based on similarity measure and discriminant feature learning
18. Hyperspectral image processing based on sparse learning and sparse graph
19. Non-convex compressed sensing framework based on block strategy and overcomplete dictionary
20. The sparse representation combined with FCM in compressed sensing
21. Compressed sensing by collaborative reconstruction
22. Hyperspectral image classification based on spectral information divergence and sparse representation




Autore

Licheng Jiao is Distinguished Professor of the School of Artificial Intelligence at Xidian University in Xi'an, China. He is IEEE Fellow, IET Fellow. He is also the vice president of CAAI, the chairman of awards and recognition committee, the Councilor of the Chinese Institute of Electronics, and an expert of academic degrees committee of the state council.
Ronghua Shang is Professor of the School of Artificial Intelligence at Xidian University. She has authored or co-authored 5 monographs and 80 papers.
Fang Liu is a Professor of the School of Artificial Intelligence at Xidian University. She has authored or co-authored over 10 monographs and over 80 papers.
Weitong Zhang is a PhD researcher in the School of Artificial Intelligence at Xidian University. Her research focuses on dynamic complex networks and she has published several papers in the field.










Altre Informazioni

ISBN:

9780128197950

Condizione: Nuovo
Dimensioni: 235 x 191 mm
Formato: Brossura
Illustration Notes:Approx. 320 illustrations (240 in full color)
Pagine Arabe: 788


Dicono di noi