list = [...
'#Linear Perceptron: percepdm', ...
'#Multilayer Perceptron for Curve Fitting: mlpdm1', ...
'#Multilayer Perceptron for Surface Fitting: mlpdm2', ...
'#Radian Basis Function Network for Curve Fitting: rbfndm1', ...
'#Kohonen Feature Map for 2D Data: kfm', ...
'#Genetic Algorithm for Finding the Maximum of the "Peaks" function: go_ga', ...
'#Random Search for Finding the Minimum of the "Peaks" function: go_rand', ...
'#Simplex Search for Finding the Minimum of the "Peaks" function: go_simp', ...
'#Simulated Annealing for the Travel Salesperson Problem: tsp', ...
'#Gradient Descent for the "Peaks" Function: sddemo', ...
'#Various Descent Directions for the "Peaks" Function: descent', ...
'#Taylor Series Approximation and Polynomial Fitting: taylor', ...
'#Printed Character Recognition (Fuzzy Logic Toolbox required): fuzpcr', ...
'#Fuzzy C-means Clustering (Fuzzy Logic Toolbox required): fcmdemo', ...
'#Trucker Backer-Upper (Fuzzy Logic Toolbox required): sltbu', ...
'#Ball and Beam System (Fuzzy Logic Toolbox required): slbb', ...
'#Single Inverted Pendulum (Fuzzy Logic Toolbox required): slcp', ...
'#Parallel Inverted Pendulum (Fuzzy Logic Toolbox required): slcpp1', ...
'#Inverse Kinematics of Two-link Robot Arm (Fuzzy Logic Toolbox required): invkine', ...
'#Ball Juggling (Fuzzy Logic Toolbox required): juggle'];
[labels, callbacks] = list2cb(list);
choices('Cool Demos', ...
'Cool Demos "Neuro-Fuzzy and Soft Computing"', ...
labels, callbacks, 1);