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www.eeworm.com/read/339665/12211206

m demolgd1.m

%DEMOLGD1 Demonstrate simple MLP optimisation with on-line gradient descent % % Description % The problem consists of one input variable X and one target variable % T with data generated by sampling X
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www.eeworm.com/read/339665/12211355

m demgp.m

%DEMGP Demonstrate simple regression using a Gaussian Process. % % Description % The problem consists of one input variable X and one target variable % T. The values in X are chosen in two separated c
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www.eeworm.com/read/339665/12211475

m demhmc2.m

%DEMHMC2 Demonstrate Bayesian regression with Hybrid Monte Carlo sampling. % % Description % The problem consists of one input variable X and one target variable % T with data generated by sampling X
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www.eeworm.com/read/339665/12211749

m demrbf1.m

%DEMRBF1 Demonstrate simple regression using a radial basis function network. % % Description % The problem consists of one input variable X and one target variable % T with data generated by sampling
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www.eeworm.com/read/253142/12242633

htm stringbufferexample.htm

Example Note: The latest versions of Firefox seem to have fixed the string concatenation problem. If you are using Firefox 1.0 or l
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www.eeworm.com/read/339239/12248233

m my_yprime_m.m

function yp = yprime(t,y) % Differential equation system for restricted three body problem. % Think of a small third body in orbit about the earth and moon. % The coordinate system moves with the e
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www.eeworm.com/read/150905/12248294

m gendats.m

%GENDATS Generation of a simple classification problem of 2 Gaussian classes % % A = GENDATS (N,K,D,LABTYPE) % % INPUT % N Dataset size, or 2-element array of class sizes (default: [50 50]
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www.eeworm.com/read/150905/12249857

m demhmc3.m

%DEMHMC3 Demonstrate Bayesian regression with Hybrid Monte Carlo sampling. % % Description % The problem consists of one input variable X and one target variable % T with data generated by sampling X
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www.eeworm.com/read/150905/12249878

m demolgd1.m

%DEMOLGD1 Demonstrate simple MLP optimisation with on-line gradient descent % % Description % The problem consists of one input variable X and one target variable % T with data generated by sampling X
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www.eeworm.com/read/150905/12249978

m demgp.m

%DEMGP Demonstrate simple regression using a Gaussian Process. % % Description % The problem consists of one input variable X and one target variable % T. The values in X are chosen in two separated c
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