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Notices and Disclaimers
Getting Technical Support
What's New
Notational Conventions
Related Information
Finding an approximate solution to a stationary nonlinear heat equation
Factoring general block tridiagonal matrices
Solving a system of linear equations with an LU-factored block tridiagonal coefficient matrix
Factoring block tridiagonal symmetric positive definite matrices
Solving a system of linear equations with a block tridiagonal symmetric positive definite coefficient matrix
Computing principal angles between two subspaces
Computing principal angles between invariant subspaces of block triangular matrices
Evaluating a Fourier integral
Using Fast Fourier Transforms for computer tomography image reconstruction
Noise filtering in financial market data streams
Using the Monte Carlo method for simulating European options pricing
Using the Black-Scholes formula for European options pricing
Multiple simple random sampling without replacement
Using a histospline technique to scale images
Speeding up Python* scientific computations
Bibliography
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What's New
The following improvements have been made in this version of the cookbook:
The Speeding up Python* scientific computations recipe explains how to benefit from NumPy* and SciPy* prebuilt with oneMKL by using the Intel® Distribution for Python*.
Parent topic: Intel® oneAPI Math Kernel Library Cookbook