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This book reports on progress in numerical methods for Lattice QCD with chiral fermions. It contains a set of pedagogical introductory articles written by experts from both the Applied Mathematics and Lattice Field Theory communities, together with detailed accounts of leading-edge algorithms for the simulation of overlap chiral fermions. Topics covered include: QCD simulations in the chiral regime; Evaluation and approximation of matrix functions; Krylov subspace methods for the iterative solution of linear systems; Eigenvalue solvers. These are complemented by a set of articles on closely related numerical and technical problems in Lattice field Theory.
This is the first book devoted entirely to total least squares. The authors give a unified presentation of the TLS problem. A description of its basic principles are given, the various algebraic, statistical and sensitivity properties of the problem are discussed, and generalizations are presented. Applications are surveyed to facilitate uses in an even wider range of applications. Whenever possible, comparison is made with the well-known least squares methods. A basic knowledge of numerical linear algebra, matrix computations, and some notion of elementary statistics is required of the reader; however, some background material is included to make the book reasonably self-contained.
Infant brain damage is a serious condition that affects millions of babies each year. The period from late gestation to the first year of life is the most critical one for the development of central and autonomous nervous systems. Medical conditions such as preterm birth may compromise brain function and the end result usually is that the baby may experience long-term neurological problems related to a wide range of psychological, physical and functional complications, with consequent life-long burdens for the individuals and their families, and a high socio-economic impact for the health care system and the whole of society. During the last years, several techniques have been employed to mo...
This book constitutes the thoroughly refereed post-proceedings of the 5th International Conference on Large-Scale Scientific Computations, LSSC 2005, held in Sozopol, Bulgaria in June 2005. The 75 revised full papers presented together with five invited papers were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections.
This book is dedicated to Prof. Peter Young on his 70th birthday. Professor Young has been a pioneer in systems and control, and over the past 45 years he has influenced many developments in this field. This volume comprises a collection of contributions by leading experts in system identification, time-series analysis, environmetric modelling and control system design – modern research in topics that reflect important areas of interest in Professor Young’s research career. Recent theoretical developments in and relevant applications of these areas are explored treating the various subjects broadly and in depth. The authoritative and up-to-date research presented here will be of interest to academic researcher in control and disciplines related to environmental research, particularly those to with water systems. The tutorial style in which many of the contributions are composed also makes the book suitable as a source of study material for graduate students in those areas.
This book constitutes the refereed proceedings of the 8th Conference on Artificial Intelligence in Medicine in Europe, AIME 2001, held in Cascais, Portugal in July 2001. The 31 revised full papers presented together with 30 posters and two invited papers were carefully reviewed and selected from 79 submissions. Among the topics addressed in their context on medical information processing are knowledge management, machine learning, data mining, decision support systems, temporal reasoning, case-based reasoning, planning and scheduling, natural language processing, computer vision, image and signal interpretation, intelligent agents, telemedicine, careflow systems, and cognitive modeling.
Application-Driven Architecture Synthesis describes the state of the art of architectural synthesis for complex real-time processing. In order to deal with the stringent timing requirements and the intricacies of complex real-time signal and data processing, target architecture styles and target application domains have been adopted to make the synthesis approach feasible. These approaches are also heavily application-driven, which is illustrated by many realistic demonstrations, used as examples in the book. The focus is on domains where application-specific solutions are attractive, such as significant parts of audio, telecom, instrumentation, speech, robotics, medical and automotive processing, image and video processing, TV, multi-media, radar, sonar. Application-Driven Architecture Synthesis is of interest to both academics and senior design engineers and CAD managers in industry. It provides an excellent overview of what capabilities to expect from future practical design tools, and includes an extensive bibliography.
This book combines technology and the medical domain. It covers advances in computer vision (CV) and machine learning (ML) that facilitate automation in diagnostics and therapeutic and preventive health care. The special focus on eXplainable Artificial Intelligence (XAI) uncovers the black box of ML and bridges the semantic gap between the technologists and the medical fraternity. Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine intends to be a premier reference for practitioners, researchers, and students at basic, intermediary levels and expert levels in computer science, electronics and communications, information technology, instrumentation and control, and electri...
This book is divided in the three main areas where Professor Antonina Starita was most active in the last period of her research activity: clustering and learning applications, biomedical applications, and motor control and evaluation. The part on clustering and learning applications opens with a contribution concerning the clustering of short-text corpora by Particle Swarm Optimization (PSO). The second contribution in this part investigates the use of Neural Networks (NN), and specifically of Recurrent NN, to interpret brain images obtained by functional Magnetic Resonance Imaging (fMRI). The first part of the book is closed by a contribution on the System for Paleographic Inspections (SPI) software suite.