Market Development in China presents the analysis of leading specialists on the causes, benefits and problems resulting from China's transition to a market economy. As the authors illustrate, it is generally recognized that in the last 25 years China has achieved a rate of economic growth unmatched in any of the world's major countries. However, this growth has been unequally shared, so that by the year 2000, China also exhibited what to many observers was an alarming degree of income inequality at individual, sectoral, and regional levels. This books deals with several facets of China's spectacular economic growth and its rising income inequality. It is shown that geographical and sectoral distribution of social services has increased the degree of inequality among Chinese households. On the positive side though, there is evidence that regionalization of commodity markets has decreased, promoting pricing equality, which is surely a cornerstone of income equality. Analysis is also presented on regional technology spillovers, rural-urban labor migration, and the relationship between FDI and the ability of state-owned enterprises to cope with the pressures of hard budget constraints. The book provides updated evidence on China's social and economic inequalities and their causes. The contributions make up a cohesive and valuable study that will appeal to scholars and researchers at many levels of academe in the fields of economics, Asian studies - and Chinese studies in particular - as well as development economists.

* Introduces the fundamental theory of vertex operator algebras and its basic techniques and examples.

* Begins with a detailed presentation of the theoretical foundations and proceeds to a range of applications.

* Includes a number of new, original results and brings fresh perspective to important works of many other researchers in algebra, lie theory, representation theory, string theory, quantum field theory, and other areas of math and physics.

An emerging interdisciplinary field of study in the realm of academia has been quantum computing and its various applications. The rapid rate of progress of this advancing technology as well as its multi-faceted nature has created a vast amount of potential research material for professionals and students in numerous disciplines. Its specific ability to improve upon traditional algorithms for image processing is seizing the attention of researchers in this field, as there remains a lack of exploration into this precise area. Examining Quantum Algorithms for Quantum Image Processing is an essential reference that provides research on quantum Fourier transform, quantum wavelet transform, and quantum wavelet packet transform as tool algorithms in image processing and quantum computing. It provides a comprehensive look into quantum image algorithms to establish frameworks of quantum image processing. While highlighting topics including geometric transformation, quantum compression ratio, and storage circuits, this book is ideally designed for researchers, scientists, developers, academicians, programmers, practitioners, engineers, and upper graduate students.

* Introduces the fundamental theory of vertex operator algebras and its basic techniques and examples. * Begins with a detailed presentation of the theoretical foundations and proceeds to a range of applications. * Includes a number of new, original results and brings fresh perspective to important works of many other researchers in algebra, lie theory, representation theory, string theory, quantum field theory, and other areas of math and physics.

An emerging interdisciplinary field of study in the realm of academia has been quantum computing and its various applications. The rapid rate of progress of this advancing technology as well as its multi-faceted nature has created a vast amount of potential research material for professionals and students in numerous disciplines. Its specific ability to improve upon traditional algorithms for image processing is seizing the attention of researchers in this field, as there remains a lack of exploration into this precise area. Examining Quantum Algorithms for Quantum Image Processing is an essential reference that provides research on quantum Fourier transform, quantum wavelet transform, and quantum wavelet packet transform as tool algorithms in image processing and quantum computing. It provides a comprehensive look into quantum image algorithms to establish frameworks of quantum image processing. While highlighting topics including geometric transformation, quantum compression ratio, and storage circuits, this book is ideally designed for researchers, scientists, developers, academicians, programmers, practitioners, engineers, and upper graduate students.