Advances in Shannon's Sampling Theory provides an up-to-date discussion of sampling theory, emphasizing the interaction between sampling theory and other branches of mathematical analysis, including the theory of boundary-value problems, frames, wavelets, multiresolution analysis, special functions, and functional analysis. The author not only traces the history and development of the theory, but also presents original research and results that have never before appeared in book form. Recent techniques covered include the Feichtinger-Gröchenig sampling theory; frames, wavelets, multiresolution analysis and sampling; boundary-value problems and sampling theorems; and special functions and sampling theorems. The book will interest graduate students and professionals in electrical engineering, communications, and applied mathematics.
Introduction and a Historical Overview. Shannon Sampling Theorem and Band-Limited Signals. Generalizations of Shannon Sampling Theorems. Sampling Theorems Associated with Sturm-Liouville Boundary-Value Problems. Sampling Theorems Associated with Self-Adjoint Boundary-Value Problems. Sampling by Using Green's Function. Sampling Theorems and Special Functions. Kramer's Sampling Theorem and Lagrange-Type Interpolation in N Dimensions. Sampling Theorems for Multidimensional Signals-The Feichtinger-Gröchenig Sampling Theory. Frames and Wavelets: A New Perspective on Sampling Theorems.