Distance determination is an essential technique in astronomy, and is briefly covered in most textbooks on astrophysics and cosmology. It is rarely covered as a coherent topic in its own right. When it is discussed the approach is frequently very dry, splitting the teaching into, for example, stars, galaxies and cosmologies, and as a consequence, books lack depth and are rarely comprehensive. Adopting a unique and engaging approach to the subject An Introduction to distance Measurement in Astronomy will take the reader on a journey from the solar neighbourhood to the edge of the Universe, discussing the range of distance measurements methods on the way. The book will focus on the physical processes discussing properties that underlie each method, rather than just presenting a collection of techniques. As well as providing the most compressive account of distance measurements to date, the book will use the common theme of distance measurement to impart basic concepts relevant to a wide variety of areas in astronomy/astrophysics. The book will provide an updated account of the progress made in a large number of subfields in astrophysics, leading to improved distance estimates particularly focusing on the underlying physics. Additionally it will illustrate the pitfalls in these areas and discuss the impact of the remaining uncertainties in the complete understanding of the Universes at large. As a result the book will not only provide a comprehensive study of distance measurement, but also include many recent advances in astrophysics.

Distance determination is an essential technique in astronomy, and is briefly covered in most textbooks on astrophysics and cosmology. It is rarely covered as a coherent topic in its own right. When it is discussed the approach is frequently very dry, splitting the teaching into, for example, stars, galaxies and cosmologies, and as a consequence, books lack depth and are rarely comprehensive. Adopting a unique and engaging approach to the subject An Introduction to distance Measurement in Astronomy will take the reader on a journey from the solar neighbourhood to the edge of the Universe, discussing the range of distance measurements methods on the way. The book will focus on the physical processes discussing properties that underlie each method, rather than just presenting a collection of techniques. As well as providing the most compressive account of distance measurements to date, the book will use the common theme of distance measurement to impart basic concepts relevant to a wide variety of areas in astronomy/astrophysics. The book will provide an updated account of the progress made in a large number of subfields in astrophysics, leading to improved distance estimates particularly focusing on the underlying physics. Additionally it will illustrate the pitfalls in these areas and discuss the impact of the remaining uncertainties in the complete understanding of the Universes at large. As a result the book will not only provide a comprehensive study of distance measurement, but also include many recent advances in astrophysics.

This volume is part of the two-volume proceedings of the 19th International Conf- ence on Artificial Neural Networks (ICANN 2009), which was held in Cyprus during September 14–17, 2009. The ICANN conference is an annual meeting sp- sored by the European Neural Network Society (ENNS), in cooperation with the - ternational Neural Network Society (INNS) and the Japanese Neural Network Society (JNNS). ICANN 2009 was technically sponsored by the IEEE Computational Intel- gence Society. This series of conferences has been held annually since 1991 in various European countries and covers the field of neurocomputing, learning systems and related areas. Artificial neural networks provide an information-processing structure inspired by biological nervous systems. They consist of a large number of highly interconnected processing elements, with the capability of learning by example. The field of artificial neural networks has evolved significantly in the last two decades, with active partici- tion from diverse fields, such as engineering, computer science, mathematics, artificial intelligence, system theory, biology, operations research, and neuroscience. Artificial neural networks have been widely applied for pattern recognition, control, optimization, image processing, classification, signal processing, etc.

Vistas in Astronomy

The authors present a broad view of astronomy without complex mathematics, yet the book discusses important concepts without simplification.