Academic literature on the topic 'Rekursiv algoritm'

Perkalian adalah operasi penting di dalam teknik informatika, misalnya pada bidang kriptografi, kriptanalisis, dan pengolahan citra. Riset-riset mengenai algoritme perkalian terus-menerus dilakukan dan dikembangkan oleh berbagai ahli dari bidang ilmu matematika, teknik informatika, hingga teknik elektro. Algoritme perkalian yang paling populer dikembangkan oleh Anatoly Karatsuba pada tahun 1960 di Uni Soviet. Meskipun telah lama dan telah banyak algoritme perkalian baru yang bermunculan, tetapi algoritme ini masih tetap menjadi pilihan untuk kategori bilangan yang berukuran sedang hingga besar. Teknik divide and conquer diterapkan pada algoritme ini untuk mempercepat proses perkalian. Kelemahan dari algoritme Karatsuba adalah proses rekursif yang terlalu banyak yang menyebabkan waktu eksekusi lebih lama. Metode Nikhilam II adalah algoritme yang dikembangkan di India dan termasuk ke dalam Matematika Weda. Umumnya, Metode Nikhilam II ini digunakan oleh orang awam di India untuk memudahkan perhitungan perkalian harian. Metode ini mampu menggantikan sebagian operasi perkalian menjadi penjumlahan, sehingga bisa lebih optimal. Dalam makalah ini, metode Nikhilam II diterapkan pada bagian base case dari algoritme Karatsuba untuk mengurangi jumlah pemanggilan rekursif. Dengan demikian, algoritme Karatsuba dapat dioptimasi dari segi waktu eksekusi. Hasilnya, algoritme baru ini mampu mengoptimasi waktu eksekusi hingga tiga kali lebih cepat dibandingkan algoritme aslinya.

Informasi berbentuk gambar yang bersifat sensitif atau rahasia, seperti data pribadi, dokumen penting yang dikirimkan melalui internet belum tentu aman dari serangan pihak luar. Kerugian yang cukup besar dapat ditimbulkan apabila data tersebut diakses dan dimanipulasi oleh orang yang tidak bertanggung jawab. Salah satu metode dalam mengamankan suatu informasi adalah kriptografi. Logistic map adalah salah satu algoritma chaos yang sering digunakan dalam kriptografi citra karena algoritma ini mampu menghasilkan deretan bilangan acak yang kompleks dengan persamaan polinomial rekursif yang sederhana. Pada penelitian ini, akan diimplementasikan algoritma chaos logistic map dan pseudo-random number generator (PRNG) dalam pengenkripsian citra. Citra input akan diubah bentuknya kedalam array lalu proses difusi dilakukan secara selektif dengan mensubstitusi 4 bit MSB setiap nilai warna citra dengan kunci logistic map. Hasil difusi tersebut akan dikonfusi dengan cara mensubstitusikan indeks arraynya dengan kunci prng sehingga didapat sebuah array baru yang teracak indeksnya. Array tersebut diubah kembali menjadi sebuah citra sehingga didapat citra terenkripsi yang aman.

In modern industrial robots the components in the transmission contain nonlinearities. These nonlinearities need to be to estimated either for better control or to use the parameters for diagnosis of the system. There is a lot of work done within system identification and mainly within the field of iterative parameter estimation.

This thesis considers recursive grey-box identification for a nonlinear model of the transmission in an industrial robot. The nonlinearities that are identified are friction, spring stiffnes, hysteresis and backlash. These nonlinearities are a part of the models that are presented in this thesis. Apart from models there is a need for some sort of algorithm for the identification and some different recursive algorithms are presented. The main subject of this thesis is the identification of parameters and the excitation signals needed for the identification of each parameter.

The models and algorithms presented in this thesis work in a principle point of view. Despite this they work in varying extent for the different types of parameters. Estimation of linear and nonlinear friction and linear spring stiffnes works relatively well. Nonlinear spring stiffnes and hysteresis have not been possible to estimate. Backlash which is estimated with a hybrid variant of a RPEM which is not fully recursive works best. When it is not possible to identify the parameters suggestions on other solutions are given, such as for example extension of the model, use of other algorithms or optimization of the excitation signal.

This thesis theoretically investigates the electronic transport properties of defective carbon nanotubes (CNTs). For the defects the focus is set to vacancy types. The calculations are performed using quantum transport theory and an underlying density-functional-based tight-binding method. Two algorithmic improvements are derived, which accelerate the common methods for quasi one-dimensional systems for the specific case of (i) randomly distributed defects and (ii) long unit cells. With this, the transmission spectrum and the conductance is calculated as a function of the CNT length, diameter, chiral angle, defect type, defect density, defect fraction, and temperature. The diffusive and the localized transport regime are described by extracting elastic mean free paths and localization lengths for metallic and semiconducting CNTs. Simple analytic models for estimating or even predicting the conductance dependence on the mentioned parameters are derived. Finally, the formation of defect-induced long-range deformations and its influence on the conductance are studied.:1 Introduction 2 Fundamentals 2.1 Carbon nanotubes 2.1.1 Structure 2.1.2 Properties 2.1.3 Defects 2.1.4 Synthesis 2.1.5 Characterization 2.1.6 Applications 2.2 Electron structure theory 2.2.1 Introduction 2.2.2 Density functional theory 2.2.3 Density-functional-based tight binding 2.2.3.1 First-order expansion 2.2.3.2 Creation of the parameter set 2.2.3.3 Second-order expansion 2.2.3.4 Usage 2.3 Electron transport 2.3.1 Equilibrium Green’s-function-based quantum transport theory 2.3.2 Transport regimes 2.3.3 Classical derivation: drift-diffusion equation with a sink 2.3.4 Quantum derivation: Dorokhov-Mello-Pereyra-Kumar theory A Improved recursive Green’s function formalism for quasi one-dimensional systems with realistic defects (J. Comput. Phys. 334 (2017), 607–619) A.1 Introduction A.2 Quantum transport theory A.3 Recursive Green’s function formalisms A.3.1 Forward iteration scheme A.3.2 Recursive decimation scheme A.3.3 Renormalization decimation algorithm A.4 Improved RGF+RDA A.5 Performance test A.5.1 Random test matrix A.5.2 Transport through carbon nanotubes A.6 Summary and conclusions B Strong localization in defective carbon nanotubes: a recursive Green’s function study (New J. Phys. 16 (2014), 123026) B.1 Introduction B.2 Theoretical framework B.2.1 Transport formalism B.2.2 Recursive Green’s function formalism B.2.3 Electronic structure B.2.4 Strong localization B.3 Modeling details of the defective system B.4 Results and discussion B.4.1 Single defects B.4.2 Randomly distributed defects B.4.3 Localization exponent B.4.4 Diameter dependence and temperature dependence of the localization exponent B.5 Summary and conclusions Supplementary material C Electronic transport in metallic carbon nanotubes with mixed defects within the strong localization regime (Comput. Mater. Sci. 138 (2017), 49–57) C.1 Introduction C.2 Theoretical framework C.3 Modeling details C.4 Results and discussion C.4.1 Conductance C.4.2 Localization exponent C.4.3 Influence of temperature C.4.4 Conductance estimation C.5 Summary and conclusions D An improved Green’s function algorithm applied to quantum transport in carbon nanotubes (arXiv: 1806.02039) D.1 Introduction D.2 Electronic transport D.3 Decimation technique and renormalization-decimation algorithm D.4 Renormalization-decimation algorithm for electrodes with long unit cells D.4.1 Surface Green’s functions D.4.2 Bulk Green’s functions and electrode density of states D.5 Complexity measure and performance test D.6 Exemplary results D.7 Summary and conclusions E Electronic transport through defective semiconducting carbon nanotubes (J. Phys. Commun. 2 (2018), 105012) E.1 Introduction E.2 Theoretical framework E.3 Modeling details E.4 Results and discussion E.4.1 Transmission and transport regimes E.4.2 Energy dependent localization exponent and elastic mean free path E.4.3 Conductance, effective localization exponent and effective elastic mean free path E.5 Summary and conclusions Supplementary material F Influence of defect-induced deformations on electron transport in carbon nanotubes (J. Phys. Commun. 2 (2018), 115023) F.1 Introduction F.2 Theory F.3 Results F.4 Summary and conclusions 3 Ongoing work 4 Summary and outlook 4.1 Summary 4.2 Outlook 5 Appendix 5.1 Bandstructure of graphene 5.2 Quantum transport theory and Landauer-Büttiker formula References List of figures List of tables Acknowledgement Selbstständigkeitserklärung Curriculum vitae List of publications
Diese Dissertation untersucht mittels theoretischer Methoden die elektronischen Transporteigenschaften von defektbehafteten Kohlenstoffnanoröhren (englisch: carbon nanotubes, CNTs). Dabei werden Vakanzen als Defekte fokussiert behandelt. Die Berechnungen werden mittels Quantentransporttheorie und einer zugrunde liegenden dichtefunktionalbasierten Tight-Binding-Methode durchgeführt. Zwei algorithmische Verbesserungen werden hergeleitet, welche die üblichen Methoden für quasi-eindimensionale Systeme für zwei spezifische Fälle beschleunigen: (i) zufällig verteilte Defekte und (ii) lange Einheitszellen. Damit werden das Transmissionsspektrum und der Leitwert als Funktion von CNT-Länge, Durchmesser, chiralem Winkel, Defekttyp, Defektdichte, Defektanteil und Temperatur berechnet. Das Diffusions- und das Lokalisierungstransportregime werden beschrieben, indem die elastische freie Weglänge und die Lokalisierungslänge für metallische und halbleitende CNTs extrahiert werden. Einfache analytische Modelle zur Abschätzung bis hin zur Vorhersage des Leitwertes in Abhängigkeit besagter Parameter werden abgeleitet. Schlussendlich werden die Bildung einer defektinduzierten, langreichweitigen Deformation und deren Einfluss auf den Leitwert studiert.:1 Introduction 2 Fundamentals 2.1 Carbon nanotubes 2.1.1 Structure 2.1.2 Properties 2.1.3 Defects 2.1.4 Synthesis 2.1.5 Characterization 2.1.6 Applications 2.2 Electron structure theory 2.2.1 Introduction 2.2.2 Density functional theory 2.2.3 Density-functional-based tight binding 2.2.3.1 First-order expansion 2.2.3.2 Creation of the parameter set 2.2.3.3 Second-order expansion 2.2.3.4 Usage 2.3 Electron transport 2.3.1 Equilibrium Green’s-function-based quantum transport theory 2.3.2 Transport regimes 2.3.3 Classical derivation: drift-diffusion equation with a sink 2.3.4 Quantum derivation: Dorokhov-Mello-Pereyra-Kumar theory A Improved recursive Green’s function formalism for quasi one-dimensional systems with realistic defects (J. Comput. Phys. 334 (2017), 607–619) A.1 Introduction A.2 Quantum transport theory A.3 Recursive Green’s function formalisms A.3.1 Forward iteration scheme A.3.2 Recursive decimation scheme A.3.3 Renormalization decimation algorithm A.4 Improved RGF+RDA A.5 Performance test A.5.1 Random test matrix A.5.2 Transport through carbon nanotubes A.6 Summary and conclusions B Strong localization in defective carbon nanotubes: a recursive Green’s function study (New J. Phys. 16 (2014), 123026) B.1 Introduction B.2 Theoretical framework B.2.1 Transport formalism B.2.2 Recursive Green’s function formalism B.2.3 Electronic structure B.2.4 Strong localization B.3 Modeling details of the defective system B.4 Results and discussion B.4.1 Single defects B.4.2 Randomly distributed defects B.4.3 Localization exponent B.4.4 Diameter dependence and temperature dependence of the localization exponent B.5 Summary and conclusions Supplementary material C Electronic transport in metallic carbon nanotubes with mixed defects within the strong localization regime (Comput. Mater. Sci. 138 (2017), 49–57) C.1 Introduction C.2 Theoretical framework C.3 Modeling details C.4 Results and discussion C.4.1 Conductance C.4.2 Localization exponent C.4.3 Influence of temperature C.4.4 Conductance estimation C.5 Summary and conclusions D An improved Green’s function algorithm applied to quantum transport in carbon nanotubes (arXiv: 1806.02039) D.1 Introduction D.2 Electronic transport D.3 Decimation technique and renormalization-decimation algorithm D.4 Renormalization-decimation algorithm for electrodes with long unit cells D.4.1 Surface Green’s functions D.4.2 Bulk Green’s functions and electrode density of states D.5 Complexity measure and performance test D.6 Exemplary results D.7 Summary and conclusions E Electronic transport through defective semiconducting carbon nanotubes (J. Phys. Commun. 2 (2018), 105012) E.1 Introduction E.2 Theoretical framework E.3 Modeling details E.4 Results and discussion E.4.1 Transmission and transport regimes E.4.2 Energy dependent localization exponent and elastic mean free path E.4.3 Conductance, effective localization exponent and effective elastic mean free path E.5 Summary and conclusions Supplementary material F Influence of defect-induced deformations on electron transport in carbon nanotubes (J. Phys. Commun. 2 (2018), 115023) F.1 Introduction F.2 Theory F.3 Results F.4 Summary and conclusions 3 Ongoing work 4 Summary and outlook 4.1 Summary 4.2 Outlook 5 Appendix 5.1 Bandstructure of graphene 5.2 Quantum transport theory and Landauer-Büttiker formula References List of figures List of tables Acknowledgement Selbstständigkeitserklärung Curriculum vitae List of publications