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E-raamat: Neural Computation and Particle Accelerators: Research, Technology and Applications

  • Formaat: 431 pages
  • Ilmumisaeg: 01-Jun-2016
  • Kirjastus: Nova Science Publishers Inc
  • ISBN-13: 9781616684655
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  • Formaat: 431 pages
  • Ilmumisaeg: 01-Jun-2016
  • Kirjastus: Nova Science Publishers Inc
  • ISBN-13: 9781616684655
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This book discusses neural computation, a network or circuit of biological neurons and relatedly, particle accelerators, a scientific instrument which accelerates charged particles such as protons, electrons and deuterons. Accelerators have a very broad range of applications in many industrial fields, from high energy physics to medical isotope production. Nuclear technology is one of the fields discussed in this book. The development that has been reached by particle accelerators in energy and particle intensity has opened the possibility to a wide number of new applications in nuclear technology. This book reviews the applications in the nuclear energy field and the design features of high power neutron sources are explained. Surface treatments of niobium flat samples and superconducting radio frequency cavities by a new technique called gas cluster ion beam are also studied in detail, as well as the process of electropolishing. Furthermore, magnetic devises such as solenoids, dipoles and undulators, which are essential components for beam orbit control in charged particle accelerators, are also examined in this book, and the important role magnetic fringe fields play in particle dynamics is explored as well. Recent development of modern ion-therapy beam delivery systems are also summarized based on the combination of the pencil-beam scanning techniques with rotating gantries. Other chapters in this book include a discussion of the dynamics of subdural EEG, a general theoretical treatment of frictional cooling and an outline of a novel laser-driven high-energy charged-particle accelerator. Also discussed are a generalized pattern search (GPS) method applied to the topological optimization of artificial neural networks (ANNs) and different applications of the Spike Timing Dependent Plasticity (STDP), a neural algorithm which operates on inter-spike intervals rate rather than firing rate. Surface treatments of niobium flat samples and superconducting radio frequency cavities by a new technique called gas cluster ion beam are studied in detail and by electropolishing are discussed briefly.
Preface vii
Chapter 1 Magnetic Fringe Fields and Interference in High-Intensity Accelerators
1(88)
J.G. Wang
Chapter 2 Transport Calculations and Accelerator Experiments Needed for Radiation Risk Assessment in Space
89(16)
L. Sihver
Chapter 3 Transport of Ion-Therapy Beams in Rotating Gantries
105(42)
Marius Pavlovic
Chapter 4 Investigation of Surface Treatments of Niobium Flat Samples and SRF Cavities by Gas Cluster Ion Beam Techique for Particle Accelerators
147(42)
A.T. Wu
D.R. Swenson
P. Kneisel
G. Wu
Z. Insepov
J. Saunders
R. Manus
B. Golden
S. Castagnola
W. Sommer
E. Harms
T. Khabiboulline
W. Murayi
H. Edwards
Chapter 5 The Roles of Chloroplast Proteases in the Assembly and Turnover of Light-Harvesting Complex
189(22)
Jie Zhang
Ning Li
Chapter 6 Design of High Power Neutron Sources for Nuclear Technology Applications by Means of Partical Accelerators
211(22)
Alberto Abanades
Chapter 7 Subdural Interictal EEG Analysis for Extracting Discriminating Features towards Electrode Classification Using Artificial Neural Networks
233(24)
Mercedes Cabrerizo
Malek Adjouadi
Melvin Ayala
Prasanna Jayakar
Chapter 8 A New Method for Preparing Submicron and Nano-Sized Aromatic Polyamide Particles with Various Morphologies and Characteristic Features
257(12)
Yayoi Yoshioka
Chapter 9 Surface Treatments of Niobium Superconduting Radio Frequency Cavities by Electropolishing for Particle Accelerators
269(6)
A.T. Wu
Chapter 10 Frictional Cooling of a Particle Beam
275(14)
H. Daniel
F.J. Hartmann
Chapter 11 Model Selection for Gaussian Mixture Model in a Two-Phase Procedure: A Further Comparative Study
289(28)
Lei Shi
Chapter 12 Principle of a Laser-Driven Charged-Particle Accelerator
317(6)
H. Daniel
Chapter 13 Topological Optimization of Artificial Neural Networks Using a Pattern Search Method
323(22)
Matthias Ihme
Chapter 14 Approximate Joint Matrix Diagonalization by Riemannian-Gradient-Based Optimization over the Unitary Group (With Application to Neural Multichannel Blind Deconvolution)
345(24)
Simone Fiori
Paola Baldassarri
Chapter 15 Spike Timing Dependent Plasticity: A Route to Robustness in Hardware and Algorithms
369(36)
Katherine Cameron
Zhijun Yang
Alan Murray
Index 405