Skip to main content Accessibility help
An Introduction to Numerical Analysis
  • Get access
    Check if you have access via personal or institutional login
  • Cited by 247
  • Cited by
    This book has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Kauffman, Justin A. George, William L. and Pitt, Jonathan S. 2019. An Overset Mesh Framework for an Isentropic ALE Navier-Stokes HDG Formulation.

    Angermann, Lutz and Yatsyk, Vasyl V. 2019. Resonant Scattering and Generation of Waves. p. 115.

    2019. Energy Transfers by Convection. p. 389.

    Gousenbourger, Pierre-Yves Massart, Estelle and Absil, P.-A. 2018. Data Fitting on Manifolds with Composite Bézier-Like Curves and Blended Cubic Splines. Journal of Mathematical Imaging and Vision,

    Zhang, Yunong Qi, Zhiyuan Li, Jian Qiu, Binbin and Yang, Min 2018. Stepsize domain confirmation and optimum of ZeaD formula for future optimization. Numerical Algorithms,

    Company, Rafael Egorova, Vera N. Jódar, Lucas and Soleymani, Fazlollah 2018. A stable local radial basis function method for option pricing problem under the Bates model. Numerical Methods for Partial Differential Equations,

    Li, Zhinian Wang, Shenliang Hong, Wei Zou, Shihui Xiao, Liping and Fan, Jie 2018. Intelligent Optimization of Na−Mn−W/SiO2 Catalysts for the Oxidative Coupling of Methane. ChemNanoMat, Vol. 4, Issue. 5, p. 487.

    Fernandes de Mello, Rodrigo and Antonelli Ponti, Moacir 2018. Machine Learning. p. 227.

    Messaoudi, Abderrahim Errachid, Mohammed Jbilou, Khalide and Sadok, Hassane 2018. GRPIA: a new algorithm for computing interpolation polynomials. Numerical Algorithms,

    Fasiolo, Matteo de Melo, Flávio Eler and Maskell, Simon 2018. Langevin incremental mixture importance sampling. Statistics and Computing, Vol. 28, Issue. 3, p. 549.

    Chen, Xi Hobson, Michael Das, Saptarshi and Gelderblom, Paul 2018. Improving the efficiency and robustness of nested sampling using posterior repartitioning. Statistics and Computing,

    Yang, Xin-She Deb, Suash Zhao, Yu-Xin Fong, Simon and He, Xingshi 2018. Swarm intelligence: past, present and future. Soft Computing, Vol. 22, Issue. 18, p. 5923.

    Herbst, Steven Lim, Byong Chan and Horowitz, Mark 2018. Fast FPGA emulation of analog dynamics in digitally-driven systems. p. 1.

    Yang, Hee Jun and Kim, Hyea Hyun 2018. A Hybrid Staggered Discontinuous Galerkin Method for KdV Equations. Journal of Scientific Computing, Vol. 77, Issue. 1, p. 502.

    Cioslowski, Jerzy and Pra̧tnicki, Filip 2018. Simpler is often better: Computational efficiency of explicitly correlated two-electron basis sets generated by the regularized Krylov sequences of Nakatsuji. The Journal of Chemical Physics, Vol. 149, Issue. 18, p. 184107.

    Pigeonneau, Franck Cornet, Alexandre and Lopépé, Fredéric 2018. Thermoconvective instabilities of a non-uniform Joule-heated liquid enclosed in a rectangular cavity. Journal of Fluid Mechanics, Vol. 843, Issue. , p. 601.

    Ha, Seung-Yeal and Zhang, Xiongtao 2018. Uniform-in-time transition from discrete dynamics to continuous dynamics in the Cucker–Smale flocking. Mathematical Models and Methods in Applied Sciences, Vol. 28, Issue. 09, p. 1699.

    Cui, Hengfei Xia, Yong Zhang, Yanning and Zhong, Liang 2018. Validation of right coronary artery lumen area from cardiac computed tomography against intravascular ultrasound. Machine Vision and Applications, Vol. 29, Issue. 8, p. 1287.

    Alevizos, Panos N. and Bletsas, Aggelos 2018. Sensitive and Nonlinear Far-Field RF Energy Harvesting in Wireless Communications. IEEE Transactions on Wireless Communications, Vol. 17, Issue. 6, p. 3670.

    Maciąg, Paweł Malczyk, Paweł and Frączek, Janusz 2018. Dynamical Systems in Applications. Vol. 249, Issue. , p. 241.


Book description

Numerical analysis provides the theoretical foundation for the numerical algorithms we rely on to solve a multitude of computational problems in science. Based on a successful course at Oxford University, this book covers a wide range of such problems ranging from the approximation of functions and integrals to the approximate solution of algebraic, transcendental, differential and integral equations. Throughout the book, particular attention is paid to the essential qualities of a numerical algorithm - stability, accuracy, reliability and efficiency. The authors go further than simply providing recipes for solving computational problems. They carefully analyse the reasons why methods might fail to give accurate answers, or why one method might return an answer in seconds while another would take billions of years. This book is ideal as a text for students in the second year of a university mathematics course. It combines practicality regarding applications with consistently high standards of rigour.


‘The book is easy to read. It flows smoothly and I would consider it to be well worth the money and a useful update to the literature.’

Source: Mathematics Today

'The book is well written and offers a good level of rigor for the intended readership … good book for mathematics students who come armed with some background in analysis.'

Eugene L. Allgower - Colorado State University

'This is an excellent book for introducing undergraduates to the fascinating discipline of numerical analysis. It is the result of many years of lectures held by the authors at the University of Oxford, a fact that explains the evident ability of the book of addressing questions frequently asked by students.'

Source: Internationale Mathematische Nachrichten

'This is a very good textbook to introduce mathematics students to numerical analysis … The authors have made a good choice of introductory topics in numerical analysis … The book is very carefully written and can indeed be recommended as a textbook for a course for second or third year mathematics students … It is a pleasure to browse through this book; it is written in a pleasant style and contains many historic references to ancient and modern mathematicians with some details about their lives.'

Source: Zentralblatt MATH

'The book is well written and offers a good level of rigor for the intended readership … This is a good book for mathematics students who come armed with some background in analysis. It is carefully written with a good level of rigor.'

Eugene L. Allgower - Colorado State University,

Refine List
Actions for selected content:
Select all | Deselect all
  • View selected items
  • Export citations
  • Download PDF (zip)
  • Send to Kindle
  • Send to Dropbox
  • Send to Google Drive
  • Send content to

    To send content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about sending content to .

    To send content items to your Kindle, first ensure is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle.

    Note you can select to send to either the or variations. ‘’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

    Find out more about the Kindle Personal Document Service.

    Please be advised that item(s) you selected are not available.
    You are about to send

Save Search

You can save your searches here and later view and run them again in "My saved searches".

Please provide a title, maximum of 40 characters.


Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Book summary page views

Total views: 0 *
Loading metrics...

* Views captured on Cambridge Core between #date#. This data will be updated every 24 hours.

Usage data cannot currently be displayed