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Thermodynamics is considered to be an offshoot of the Industrial Revo­ lution that began in England in the second half of the 18th Century and from there spread to other parts of the world. The word thermodynamics is derived from the Greek therme (meaning heat) and dynamis (meaning force). As well known, the origins of thermodynamics are founded in the early 19th century in the study of the motive power of heat; that is, the capability of hot bodies to produce mechanical work. However, there are of course precursors to these ideas: Temperature is probably the earliest thermodynamic concept to attain operational status (early in the 17th century with Galileo). The science of calorimetry beginning in the late 18th century (contemporary with the beginning of the Indus­ trial Revolution) led to the establishment of the caloric theory of heat [5]. Clausius in the second half of the 19th century established Thermody­ namics as a clearly defined science. The connection of Thermodynamics with Mechanics is first achieved through kinetic theory with the work of D. Bernouilli, J Herapath, ]. ]. Waterston, R. Clausius, ]. c. Maxwell, and finally L. Boltzmann, later through Statistical Mechanics, whose main purpose is to determine the thermodynamic properties and values of macroscopic observables in terms of the dynamical laws that govern the motion of the constitutive particles of the system. It is not easy to estab­ lish precisely the dates of the birth of Statistical Mechanics.

While wavelets have since their discovery mainly been applied to problems in signal analysis and image compression, their analytic power has more and more also been recognized for problems in Numerical Analysis. Together with the functional analytic framework for different differential and integral quations, one has been able to conceptu­ ally discuss questions which are relevant for the fast numerical solution of such problems: preconditioning issues, derivation of stable discretizations, compression of fully popu­ lated matrices, evaluation of non-integer or negative norms, and adaptive refinements based on A-posteriori error estimators. This research monograph focusses on applying wavelet methods to elliptic differential equations. Particular emphasis is placed on the treatment of the boundary and the boundary conditions. Moreover, a control problem with an elliptic boundary problem as contraint serves as an example to show the conceptual strengths of wavelet techniques for some of the above mentioned issues. At this point, I would like to express my gratitude to several people before and during the process of writing this monograph. Most of all, I wish to thank Prof. Dr. Wolfgang Dahmen to whom I personally owe very much and with whom I have co-authored a large part of my work. He is responsible for the very stimulating and challenging scientific atmosphere at the Institut fiir Geometrie und Praktische Mathematik, RWTH Aachen. We also had an enjoyable collaboration with Prof. Dr. Reinhold Schneider from the Technical University of Chemnitz.