An object-oriented method is presented that computes without truncation error derivatives of functions defined by MATLAB computer codes. The method implements forward mode automatic differentiation via operator overloading in a manner that produces a new MATLAB code which computes the derivatives of the outputs of the original function with respect to the variables of differentiation. Because the derivative code has the same input as the original function code, the method can be used recursively to generate derivatives of any order that are desired. In addition, the approach developed in this paper has the feature that the derivatives are generated simply by evaluating the function on an instance of the class, thus making the method straigh...
Automatic dierentiation is introduced as a powerful technique to compute deriva-tives of functions g...
In this paper, we introduce automatic differentiation as a method for computing derivatives of large...
In engineering applications, we often need the derivatives of functions defined by a program. The ap...
An object-oriented method is presented that generates derivatives of functions defined by MATLAB com...
A new object-oriented method is presented for generating analytic derivatives of func-tions defined ...
The interactive programming environment MATLAB is increasingly gaining popularity by enabling the us...
The Mad package described here facilitates the evaluation of first derivatives of multi-dimensional...
We present an example of the science that is enabled by object-oriented programming techniques. Scie...
Automatic differentiation of third order derivatives is implemented in C++. The implementation uses ...
Operator overloading in Matlab allows for user-defined types to semantically augment existing Matlab...
Abstract. This report describes MSAD, a tool that applies source transformation automatic differenti...
AbstractIn a recent paper an algorithm FEED was introduced for the systematic exact evaluation of hi...
In mathematics and computer algebra, automatic differentiation (AD) is a set of techniques to evalua...
Abstract: Numerical approaches of ordinary differential equations (ODEs) usually require Jacobian ev...
Mad is a Matlab library of functions and utilities for the automatic differentiation of Matlab func-...
Automatic dierentiation is introduced as a powerful technique to compute deriva-tives of functions g...
In this paper, we introduce automatic differentiation as a method for computing derivatives of large...
In engineering applications, we often need the derivatives of functions defined by a program. The ap...
An object-oriented method is presented that generates derivatives of functions defined by MATLAB com...
A new object-oriented method is presented for generating analytic derivatives of func-tions defined ...
The interactive programming environment MATLAB is increasingly gaining popularity by enabling the us...
The Mad package described here facilitates the evaluation of first derivatives of multi-dimensional...
We present an example of the science that is enabled by object-oriented programming techniques. Scie...
Automatic differentiation of third order derivatives is implemented in C++. The implementation uses ...
Operator overloading in Matlab allows for user-defined types to semantically augment existing Matlab...
Abstract. This report describes MSAD, a tool that applies source transformation automatic differenti...
AbstractIn a recent paper an algorithm FEED was introduced for the systematic exact evaluation of hi...
In mathematics and computer algebra, automatic differentiation (AD) is a set of techniques to evalua...
Abstract: Numerical approaches of ordinary differential equations (ODEs) usually require Jacobian ev...
Mad is a Matlab library of functions and utilities for the automatic differentiation of Matlab func-...
Automatic dierentiation is introduced as a powerful technique to compute deriva-tives of functions g...
In this paper, we introduce automatic differentiation as a method for computing derivatives of large...
In engineering applications, we often need the derivatives of functions defined by a program. The ap...