Iterative Verfahren der Numerik HS 2013 Prof. M. Grote / L. Gaudio
... The command spdiags creates a sparse matrix with the entries from the vector (passed as the first variable) on the diagonal indicated by the second variable. These variables can be passed individually or in groups as in the above example. The final two variables represent the size of the matrix. Loo ...
... The command spdiags creates a sparse matrix with the entries from the vector (passed as the first variable) on the diagonal indicated by the second variable. These variables can be passed individually or in groups as in the above example. The final two variables represent the size of the matrix. Loo ...
Maths Workshop
... Research shows that despite this some children found certain methods difficult, forgot them rather quickly or made persistent errors. ...
... Research shows that despite this some children found certain methods difficult, forgot them rather quickly or made persistent errors. ...
A Brief History of Pi
... A Brief History of Pi Ancient civilizations knew that there was a fixed ratio of circumference to diameter that was approximately equal to three. The Greeks refined the process and Archimedes is credited with the first theoretical calculation of Pi. In 1761 Lambert proved that Pi was irrational, tha ...
... A Brief History of Pi Ancient civilizations knew that there was a fixed ratio of circumference to diameter that was approximately equal to three. The Greeks refined the process and Archimedes is credited with the first theoretical calculation of Pi. In 1761 Lambert proved that Pi was irrational, tha ...
Section 5.3 Properties of Logarithms
... IV. Applications of Properties of Logarithms (Page 388) One way of finding a model for a set of nonlinear data is to take the natural log of each of the x-values and y-values of the data set. If the points are graphed and fall on a straight line, then the x-values and the y-values are related by the ...
... IV. Applications of Properties of Logarithms (Page 388) One way of finding a model for a set of nonlinear data is to take the natural log of each of the x-values and y-values of the data set. If the points are graphed and fall on a straight line, then the x-values and the y-values are related by the ...
Functional decomposition
Functional decomposition refers broadly to the process of resolving a functional relationship into its constituent parts in such a way that the original function can be reconstructed (i.e., recomposed) from those parts by function composition. In general, this process of decomposition is undertaken either for the purpose of gaining insight into the identity of the constituent components (which may reflect individual physical processes of interest, for example), or for the purpose of obtaining a compressed representation of the global function, a task which is feasible only when the constituent processes possess a certain level of modularity (i.e., independence or non-interaction). Interactions between the components are critical to the function of the collection. All interactions may not be observable, but possibly deduced through repetitive perception, synthesis, validation and verification of composite behavior.