How Long to Read Approximation Theory and Algorithms for Data Analysis

How Long Does it Take to Read Approximation Theory and Algorithms for Data Analysis?

It takes the average reader 6 hours and 9 minutes to read Approximation Theory and Algorithms for Data Analysis by Armin Iske

Assuming a reading speed of 250 words per minute. Learn more

Description

This textbook offers an accessible introduction to the theory and numerics of approximation methods, combining classical topics of approximation with recent advances in mathematical signal processing, and adopting a constructive approach, in which the development of numerical algorithms for data analysis plays an important role. The following topics are covered: * least-squares approximation and regularization methods * interpolation by algebraic and trigonometric polynomials * basic results on best approximations * Euclidean approximation * Chebyshev approximation * asymptotic concepts: error estimates and convergence rates * signal approximation by Fourier and wavelet methods * kernel-based multivariate approximation * approximation methods in computerized tomography Providing numerous supporting examples, graphical illustrations, and carefully selected exercises, this textbook is suitable for introductory courses, seminars, and distance learning programs on approximation for undergraduate students.

How long is Approximation Theory and Algorithms for Data Analysis?

Approximation Theory and Algorithms for Data Analysis by Armin Iske is 358 pages long, and a total of 92,364 words.

This makes it 121% the length of the average book. It also has 113% more words than the average book.

How Long Does it Take to Read Approximation Theory and Algorithms for Data Analysis Aloud?

The average oral reading speed is 183 words per minute. This means it takes 8 hours and 24 minutes to read Approximation Theory and Algorithms for Data Analysis aloud.

What Reading Level is Approximation Theory and Algorithms for Data Analysis?

Approximation Theory and Algorithms for Data Analysis is suitable for students ages 12 and up.

Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.

When deciding what to show young students always use your best judgement and consult a professional.

Where Can I Buy Approximation Theory and Algorithms for Data Analysis?

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