---

Knowledge can be modeled and computed using computational mathematical methods, then lead to real world conclusions. This book examines a wide array of topics in computational analysis.

---

Introduction.- Convex Probabilistic Wavelet like Approximation.- Bidimensional Constrained Wavelet like Approximation.- Multidimensional Probabilistic Scale Approximation.- Multidimensional probabilistic approximation in wavelet like structure.- About L-Positive Approximations: About Shape Preserving Weighted Uniform Approximation.- Jackson-Type Nonpositive Approximations for Definite Integrals.- Discrete Best L1 Approximation using the Gauges Way.- Quantitative Uniform Convergence of Smooth Picard Singular Integral Operators.- Global Smoothness and Simultaneous Approximation by Smooth Picard Singular Operators.- Convergence Results.- Approximation with Rates by Fractional Smooth Picard.- Singular Operators.- Multivariate Generalized Picard Singular Integral Operators.- Approximation by q-Gauss-Weierstrass Singular Integral Operators.- Quantitative Approximation by Univariate Shift-Invariant.- Integral Operators.

---

From the reviews:

"G. A. Anastassiou is a very prolific author. His work, which has appeared in 83 papers and books during the period 1990-2010, is restructured and completed to form the 45 chapters (plus an introductory survey) of this monograph. Each chapter is self-contained and can be read independently. ... The book has the advantage of bringing together the work of the author in a systematic way, and hence it is quite useful for researchers working in this direction." (A. Bultheel, Mathematical Reviews, January, 2013)

---