Applied Harmonic Analysis Conference

Applied and Computational Harmonic Analysis is an interdisciplinary branch of modern mathematics and is concerned with the applied and computational aspects of harmonic analysis and approximation theory, with special emphasis on wavelet analysis, time-frequency analysis, redundant representations, and their applications in many areas such as signal / image processing, computer graphics, and numerical algorithms in scientific computing. Many problems in sciences and applications are multiscale in nature. One of the core goals of applied and computational harmonic analysis is to develop and study various mathematical multiscale based methods that can represent and approximate a given set of functions / signals / data efficiently and sparsely with fast algorithms. For example, signals with multiscale structure have sparse representations with respect to wavelet bases and this makes wavelet analysis a desired tool in many areas of sciences and applications. The impact of applied and computational harmonic analysis has been evidenced by many successes: wavelet based methods for image compression standard JPEG 2000 and for signal / image denoising, subdivision scheme based methods in computer graphics and visualization / simulation in medical imaging and movie / game industry, new efficient Sigma-delta schemes in analog-to-digital conversion in signal processing, adaptive wavelet methods in scientific computing for the numerical solution to partial differential equations (PDEs).