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  • © 2011

Intelligent Mathematics: Computational Analysis

  • Basic book on Intelligent Mathematics: Computational Analysis
  • Presents the Principles of Computational Analysis related to Intelligent systems
  • Written by a leading expert in the field

Part of the book series: Intelligent Systems Reference Library (ISRL, volume 5)

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Table of contents (46 chapters)

  1. Front Matter

  2. Introduction

    • George A. Anastassiou
    Pages 1-11
  3. Convex Probabilistic Wavelet Like Approximation

    • George A. Anastassiou
    Pages 13-27
  4. Bidimensional Constrained Wavelet Like Approximation

    • George A. Anastassiou
    Pages 29-40
  5. Multidimensional Probabilistic Scale Approximation

    • George A. Anastassiou
    Pages 41-56
  6. About L-Positive Approximations

    • George A. Anastassiou
    Pages 69-87
  7. About Shape Preserving Weighted Uniform Approximation

    • George A. Anastassiou
    Pages 89-91
  8. Discrete Best L1 Approximation Using the Gauges Way

    • George A. Anastassiou
    Pages 99-113
  9. A Generalized Shisha - Mond Type Inequality

    • George A. Anastassiou
    Pages 273-274

About this book

<body>Knowledge can be modeled and computed using computational mathematical methods, then lead to real world conclusions. The strongly related to that Computational Analysis is a very large area with lots of applications. This monograph includes a great variety of topics of Computational Analysis. We present: probabilistic wavelet approximations, constrained abstract approximation theory, shape preserving weighted approximation, non positive approximations to definite integrals, discrete best approximation, approximation theory of general Picard singular operators including global smoothness preservation property, fractional singular operators. We also deal with non-isotropic general Picard singular multivariate operators and q-Gauss-Weierstrass singular q-integral operators. We talk about quantitative approximations by shift-invariant univariate and multivariate integral operators, nonlinear neural networks approximation, convergence with rates of positive linear operators, quantitative approximation by bounded linear operators, univariate and multivariate quantitative approximation by stochastic positive linear operators on univariate and multivariate stochastic processes. We further present right fractional calculus and give quantitative fractional Korovkin theory of positive linear operators. We also give analytical inequalities, fractional Opial inequalities, fractional identities and inequalities regarding fractional integrals. We further deal with semi group operator approximation, simultaneous Feller probabilistic approximation. We also present Fuzzy singular operator approximations. We give transfers from real to fuzzy approximation and talk about fuzzy wavelet and fuzzy neural networks approximations, fuzzy fractional calculus and fuzzy Ostrowski inequality. We talk about discrete fractional calculus, nabla discrete fractional calculus and inequalities. We study the q-inequalities, and q-fractional inequalities. We further study time scales: delta and nabla approaches, duality principle and inequalities. We introduce delta and nabla time scales fractional calculus and inequalities. We finally study convergence with rates of approximate solutions to exact solution of multivariate Dirichlet problem and multivariate heat equation, and discuss the uniqueness of solution of general evolution partial differential equation \ in multivariate time. The exposed results are expected to find applications to: applied and computational mathematics, stochastics, engineering, artificial intelligence, vision, complexity and machine learning. This monograph is suitable for graduate students and researchers.</body>

Reviews

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)

Authors and Affiliations

  • Department of Mathematical Sciences , University of Memphis, Memphis, USA

    George A. Anastassiou

Bibliographic Information

  • Book Title: Intelligent Mathematics: Computational Analysis

  • Authors: George A. Anastassiou

  • Series Title: Intelligent Systems Reference Library

  • DOI: https://doi.org/10.1007/978-3-642-17098-0

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer Berlin Heidelberg 2011

  • Hardcover ISBN: 978-3-642-17097-3Published: 15 December 2010

  • Softcover ISBN: 978-3-642-43658-1Published: 11 October 2014

  • eBook ISBN: 978-3-642-17098-0Published: 19 March 2011

  • Series ISSN: 1868-4394

  • Series E-ISSN: 1868-4408

  • Edition Number: 1

  • Number of Pages: XVII, 802

  • Topics: Computational Intelligence, Artificial Intelligence

Buy it now

Buying options

eBook USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access