The fourth volume of the Collected Works is devoted to Wigners contribution to physical chemistry, statistical mechanics and solid-state physics. One corner stone was his introduction of what is now called the Wigner function, while his paper on adiabatic perturbations foreshadowed later work on Berry phases. Although few in number, Wigners articles on solid-state physics laid the foundations for the modern theory of the electronic structure of metals.

The first broad account offering a non-mathematical, unified treatment of solid state chemistry. Describes synthetic methods, X-ray diffraction, principles of inorganic crystal structures, crystal chemistry and bonding in solids; phase diagrams of 1, 2 and 3 component systems; the electrical, magnetic, and optical properties of solids; three groups of industrially important inorganic solids--glass, cement, and refractories; and certain aspects of organic solid state chemistry, including the ``organic metal'' of new materials.

Eugene Wigner is one of the few giants of 20th-century physics. The present annotated volume begins with a short biographical sketch followed by Wigner's papers on group theory, an extremely powerful tool he created for theoretical quantum physics.

Eugene Wigner is one of the few giants of 20th-century physics. The present annotated volume begins with a short biographical sketch followed by Wigner's papers on group theory, an extremely powerful tool he created for theoretical quantum physics.

E.P. Wigner, one of the leading scientists involved in the early development of nuclear technology, had always in mind its political and social implications. In the 60s persuing his goal of a peaceful open world he began to develop the concept of Civil Defense against nuclear attacks. Looking back one might see this as an alternative to the concept of the Nuclear Shield. The present volume contains a selection of Wigner's writings on this subject. It is annotated by Conrad Chester.

Among the founding fathers of modern quantum physics few have contributed to our basic understanding of its concepts as much as E.P. Wigner. His articles on the epistemology of quantum mechanics and the measurement problem, and the basic role of symmetries were of fundamental importance for all subsequent work. He was also the first to discuss the concept of consciousness from the point of view of modern physics. G.G. Emch edited most of those papers and wrote a very helpful introduction into Wigner's contributions to Natural Philosophy. The book should be a gem for all those interested in the history and philosophy of science.

Eugene Wigner is one of the very few scientists that may safely be describedas creators of 20th-century physics. This volume of his Collected Works is devoted to his contributions to nuclear energy. In his Introduction and Annotations A.M. Weinberg surveys Wigner's contributions to nuclear-reaction physics and nuclear engineering, at the same time giving a glimpse of the early history of nuclear-reactor technology. Wigner himself gave a lively and critical account, which is published in this volume for the first time. Furthermore the book contains forty-two reports and memoranda from 1941 to 1945 and twelve of Wigner's many patents relating to nuclear energy.

This 21st Century Nanoscience Handbook will be the most comprehensive, up-to-date large reference work for the field of nanoscience. Handbook of Nanophysics, by the same editor, published in the fall of 2010, was embraced as the first comprehensive reference to consider both fundamental and applied aspects of nanophysics. This follow-up project has been conceived as a necessary expansion and full update that considers the significant advances made in the field since 2010. It goes well beyond the physics as warranted by recent developments in the field. Key Features: Provides the most comprehensive, up-to-date large reference work for the field. Chapters written by international experts in the field. Emphasises presentation and real results and applications. This handbook distinguishes itself from other works by its breadth of coverage, readability and timely topics. The intended readership is very broad, from students and instructors to engineers, physicists, chemists, biologists, biomedical researchers, industry professionals, governmental scientists, and others whose work is impacted by nanotechnology. It will be an indispensable resource in academic, government, and industry libraries worldwide. The fields impacted by nanoscience extend from materials science and engineering to biotechnology, biomedical engineering, medicine, electrical engineering, pharmaceutical science, computer technology, aerospace engineering, mechanical engineering, food science, and beyond.

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques: A MATLAB Based Approach presents how machine learning and biomedical signal processing methods can be used in biomedical signal analysis. Different machine learning applications in biomedical signal analysis, including those for electrocardiogram, electroencephalogram and electromyogram are described in a practical and comprehensive way, helping readers with limited knowledge. Sections cover biomedical signals and machine learning techniques, biomedical signals, such as electroencephalogram (EEG), electromyogram (EMG) and electrocardiogram (ECG), different signal-processing techniques, signal de-noising, feature extraction and dimension reduction techniques, such as PCA, ICA, KPCA, MSPCA, entropy measures, and other statistical measures, and more. This book is a valuable source for bioinformaticians, medical doctors and other members of the biomedical field who need a cogent resource on the most recent and promising machine learning techniques for biomedical signals analysis. - Provides comprehensive knowledge in the application of machine learning tools in biomedical signal analysis for medical diagnostics, brain computer interface and man/machine interaction - Explains how to apply machine learning techniques to EEG, ECG and EMG signals - Gives basic knowledge on predictive modeling in biomedical time series and advanced knowledge in machine learning for biomedical time series