Brain and nature-inspired learning, computation and recognition /

Bibliographic Details
Main Authors:	Jiao, Li-cheng (Author), Shang, Ronghua (Author), Liu, Fang (Author), Zhang, Weitong (Author)
Corporate Author:	ScienceDirect (Online service)
Format:	eBook
Language:	English
Published:	Amsterdam, Netherlands : Elsevier, 2020.
Subjects:	Natural computation. Calcul naturel. Natural computation Neural Networks, Computer Machine Learning Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

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