The GP kernel is a C++ class library that can be used to apply genetic
programming techniques to all kinds of problems. The library defines
a class hierarchy. An integral component is the ability to produce
automatically defined functions as found in Koza s "Genetic
Programming II".
At can be given its arguments in a file. You can comment
out lines by preceding them with either # or -
characters. This is an easy way to temporarily disable
some commands.
The CONTINUE-command is most useful at the end of the
file. When this command is read, the file is started
again from the beginning. You can use it situations where
the machine is not shut down for the night and you want
to run some commands every day.
simulating a convolutional encoder
allows the user to input a source code to be encoded and also input the values of the generator polynomials. It outputs the encoded data bits, where 1/n is the code rate
This GUI can be used by entering nu at the MATLAB command prompt. The user can either select a function (f(x)) of their choice or a statistical distribution probability distribution function to plot over a user defined range. The function s integral can be evaluated over a user defined range by using: The composite trapezium, simpsons and gauss-legendre rules. This is useful for calculating accurate probabilities that one might see in statistical tables.
These instances, whenmapped to an N-dimensional space, represent a core set that can be
used to construct an approximation to theminimumenclosing ball. Solving the SVMlearning
problem on these core sets can produce a good approximation solution in very fast speed.
For example, the core-vector machine [81] thus produced can learn an SVM for millions of
data in seconds.
