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StepMonitor   (Built-in Mathematica Symbol)
StepMonitor is an option for iterative numerical computation functions that gives an expression to evaluate whenever a step is taken by the numerical method used.
Approximate Functions and Interpolation   (Mathematica Tutorial)
In many kinds of numerical computations, it is convenient to introduce approximate functions. Approximate functions can be thought of as generalizations of ordinary ...
Basic Objects   (Mathematica Tutorial)
Expressions are the main type of data in Mathematica. Expressions can be written in the form h[e_1,e_2,…]. The object h is known generically as the head of the expression. ...
Linear IVPs and BVPs   (Mathematica Tutorial)
To begin, consider an initial value problem for a linear first-order ODE. This is a linear first-order ODE. Notice that the general solution is a linear function of the ...
Installing MathLM   (Mathematica Tutorial)
MathLM is available for Windows, Linux, and Mac OS X. For a detailed list of specific platforms, visit www.wolfram.com/mathematica/features/system-requirements.html. Each ...
Launching MathLM   (Mathematica Tutorial)
Once installed, MathLM starts running automatically by default each time the machine is rebooted. To start or stop MathLM manually, follow these instructions. It is assumed ...
Symbolic Evaluation   (Mathematica Tutorial)
The functions FindMinimum, FindMaximum, and FindRoot have the HoldAll attribute and so have special semantics for evaluation of their arguments. First, the variables are ...
Compiling Mathematica Expressions   (Mathematica Tutorial)
If you make a definition like f[x_]:=x Sin[x], Mathematica will store the expression x Sin[x] in a form that can be evaluated for any x. Then when you give a particular value ...
Manipulating Equations and Inequalities   (Mathematica Overview)
Equations Solving Equations The Representation of Equations and Solutions
Function Approximations Package   (Function Approximations Package Tutorial)
This loads the package. Economized rational approximations. A Pad é approximation is very accurate near the center of expansion, but the error increases rapidly as you get ...
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