LEADER 01752nam 2200361 450 001 9910688461703321 005 20230628221141.0 035 $a(CKB)5400000000043932 035 $a(NjHacI)995400000000043932 035 $a(EXLCZ)995400000000043932 100 $a20230628d2020 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aProcessing and Analysis of Hyperspectral Data /$fJie Chen, Yingying Song, Hengchao Li 210 1$aLondon :$cIntechOpen,$d2020. 215 $a1 online resource (136 pages) 311 $a1-83880-462-5 330 $aHyperspectral imagery has received considerable attention in the last decade as it provides rich spectral information and allows the analysis of objects that are unidentifiable by traditional imaging techniques. It has a wide range of applications, including remote sensing, industry sorting, food analysis, biomedical imaging, etc. However, in contrast to RGB images from which information can be intuitively extracted, hyperspectral data is only useful with proper processing and analysis. This book covers theoretical advances of hyperspectral image processing and applications of hyperspectral processing, including unmixing, classification, super-resolution, and quality estimation with classical and deep learning methods. 606 $aSpectrum analysis 615 0$aSpectrum analysis. 676 $a535.84 700 $aChen$b Jie$01299851 702 $aSong$b Yingying 702 $aLi$b Hengchao 801 0$bNjHacI 801 1$bNjHacl 906 $aBOOK 912 $a9910688461703321 996 $aProcessing and Analysis of Hyperspectral Data$93394347 997 $aUNINA LEADER 01251nam0 22002891i 450 001 UON00217754 005 20231205103401.282 010 $a97-267-4022-3 100 $a20030730d1992 |0itac50 ba 101 $apor 102 $aPT 105 $a|||| 1|||| 200 1 $aDidáctica do Português$fCarlos Reis, José Victor Adragao$gcom a colaboraçao de Maria Alice Sousa Martins, Maria do Rosário Vaz 210 $aLisboa$cUniversidade Aberta$d1992. 206 p. ; 30 cm. 410 1$1001UON00172841$12001 $a Textos de base$1210 $aLisboa$cUniversidade Aberta$v17 606 $aLINGUA PORTOGHESE$xInsegnamento$3UONC041501$2FI 620 $aPT$dLisboa$3UONL003135 676 $a469.07$cLingua portoghese. Studio e insegnamento$v21 700 1$aREIS$bCarlos$3UONV108386$0157373 701 1$aADRAGAO$bJosé Víctor$3UONV131977$0595686 712 $aUniversidade Aberta$3UONV266267$4650 801 $aIT$bSOL$c20240220$gRICA 899 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$2UONSI 912 $aUON00217754 950 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$dSI Port 6 U.A 017 $eSI LO 64860 5 017 996 $aDidáctica do português$9992174 997 $aUNIOR LEADER 03899nam 22007335 450 001 9910857790203321 005 20250807135553.0 010 $a3-031-55076-5 024 7 $a10.1007/978-3-031-55076-8 035 $a(CKB)32027838900041 035 $a(MiAaPQ)EBC31340825 035 $a(Au-PeEL)EBL31340825 035 $a(MiAaPQ)EBC31339989 035 $a(Au-PeEL)EBL31339989 035 $a(DE-He213)978-3-031-55076-8 035 $a(EXLCZ)9932027838900041 100 $a20240513d2024 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aComplex and Adaptive Dynamical Systems $eA Comprehensive Introduction /$fby Claudius Gros 205 $a5th ed. 2024. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2024. 215 $a1 online resource (468 pages) 311 08$a3-031-55075-7 327 $aNetwork Theory -- Bifurcations and Chaos in Dynamical Systems -- Dissipation, Noise and Adaptive Systems -- Self Organization -- Information Theory of Complex Systems -- Self-Organized Criticality -- Random Boolean Networks -- Darwinian Evolution, Hypercycles and Game Theory -- Synchronization Phenomena -- Complexity of Machine Learning -- Solutions. 330 $aThis textbook offers a comprehensive introduction to the concepts underpinning our modern understanding of complex and emergent behavior. Mathematical methods necessary for the discussion are introduced and explained on the run. All derivations are presented step-by-step. This new fifth edition has been fully revised and includes a new chapter, a range of new sections, figures and exercises. The Solution chapter has been reorganized for clarity. The core aspects of modern complex system sciences are presented in the first chapters, covering the foundations of network- and dynamical system theory, with a particular focus on scale-free networks and tipping phenomena. The notion of deterministic chaos is treated together with bifurcation theory and the intricacies of time delays. Modern information theoretical principles are discussed in further chapters, together with the notion of self-organized criticality, synchronization phenomena, and a game-theoretical treatment of the tragedy of the commons. The dynamical systems view of modern machine learning is presented in a new chapter. Chapters include exercises and suggestions for further reading. The textbook is suitable for graduate and advanced undergraduate students. The prerequisites are the basic mathematical tools of courses in natural sciences, computer science or engineering. 606 $aSystem theory 606 $aDynamics 606 $aNonlinear theories 606 $aGraph theory 606 $aDynamics 606 $aNeural networks (Computer science) 606 $aStochastic processes 606 $aComplex Systems 606 $aApplied Dynamical Systems 606 $aGraph Theory 606 $aDynamical Systems 606 $aMathematical Models of Cognitive Processes and Neural Networks 606 $aStochastic Networks 615 0$aSystem theory. 615 0$aDynamics. 615 0$aNonlinear theories. 615 0$aGraph theory. 615 0$aDynamics. 615 0$aNeural networks (Computer science) 615 0$aStochastic processes. 615 14$aComplex Systems. 615 24$aApplied Dynamical Systems. 615 24$aGraph Theory. 615 24$aDynamical Systems. 615 24$aMathematical Models of Cognitive Processes and Neural Networks. 615 24$aStochastic Networks. 676 $a530.1 700 $aGros$b Claudius$0792256 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910857790203321 996 $aComplex and Adaptive Dynamical Systems$91771522 997 $aUNINA