What are some recommended textbooks for implementing numerical algorithms?

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In summary, the individual is looking for recommendations on numerical methods books that cover topics such as root-finding, numerical integration, and numerical interpolation. They were considering purchasing "Numerical Recipes" but discovered that it is copyrighted and therefore illegal to use. They are seeking a book that covers a wide range of topics and includes detailed theory on stability, convergence, etc. They currently have the first edition of "Stoer and Bulirsch," which they find to be challenging to read but appreciate its approach of motivating mathematical results before discussing solution approaches and their properties.
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Somefantastik
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Maybe I missed the numerical methods books in the textbook forum? But I'd like a few suggestions on good texts that are descriptive in implementing numerical algorithms like root-finding, numerical integration, numerical interpolation, etc. I was about to buy Numerical Recipes

But I noticed in the comments that the algorithms are copyrighted.. so it's straight-up illegal to use that book in practice. There's hundreds of numerical methods books on amazon, can someone suggest one that they found useful? I have my undergrad book, which is TOO undergrad. I also have many books on FEM and numerical linear algebra, so I'm looking for one that covers a more general swath of topics. It must give detailed theory of stability, convergence, etc.
 
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I have the first edition of Stoer and Bulirsch. It's not the easiest book to read because it assumes some mathematical sophistication, but it does motivate the math results before discussing solution approaches and their properties and behaviors.
 

Related to What are some recommended textbooks for implementing numerical algorithms?

1. What are numerical methods/algorithms?

Numerical methods/algorithms are mathematical techniques used to solve problems that cannot be solved analytically, such as differential equations or optimization problems. They involve using numerical approximations and calculations to find solutions to these problems.

2. What are some common examples of numerical methods/algorithms?

Some common examples of numerical methods/algorithms include the Newton-Raphson method for finding roots of equations, the Gaussian elimination method for solving systems of linear equations, and the Euler method for solving differential equations.

3. How are numerical methods/algorithms used in scientific research?

Numerical methods/algorithms are used in scientific research to solve complex problems that cannot be solved analytically. They are particularly useful in fields such as physics, engineering, and finance where there are many real-world problems that require numerical solutions.

4. What are the advantages of using numerical methods/algorithms?

The advantages of using numerical methods/algorithms include their ability to solve complex problems quickly and accurately, their ability to handle large and complicated data sets, and their flexibility in adapting to different types of problems.

5. What are the limitations of numerical methods/algorithms?

Some limitations of numerical methods/algorithms include their dependence on initial conditions and assumptions, their susceptibility to rounding errors and instability, and their inability to find exact solutions to problems. Additionally, some problems may require a high level of computational resources to solve using numerical methods/algorithms.

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