Neural Network Toolbox

Demonstrations and Applications

Tables of Demonstrations and Applications

Chapter 2: Neuron Model and Network Architectures

	Filename	Page
Simple neuron and transfer functions	nnd2n1	page 2-5
Neuron with vector input	nnd2n2	page 2-7

Chapter 3: Perceptrons

	Filename	Page
Decision boundaries	nnd4db	page 3-5
Perceptron learning rule. Pick boundaries	nnd4pr	page 3-15
Classification with a two-input perceptron	demop1	page 3-20
Outlier input vectors	demop4	page 3-21
Normalized perceptron rule	demop5	page 3-22
Linearly nonseparable vectors	demop6	page 3-21

Chapter 4: Linear Filters

	Filename	Page
Pattern association showing error surface	demolin1	page 4-9
Training a linear neuron	demolin2	page 4-17
Linear classification system	nnd10lc	page 4-17
Linear fit of nonlinear problem	demolin4	page 4-18
Underdetermined problem	demolin5	page 4-18
Linearly dependent problem	demolin6	page 4-19
Too large a learning rate	demolin7	page 4-19

Chapter 5: Backpropagation

	Filename	Page
Generalization	nnd11gn	page 5-51
Steepest descent backpropagation	nnd12sd1	page 5-11
Momentum backpropagation	nnd12mo	page 5-13
Variable learning rate backpropagation	nnd12vl	page 5-15
Conjugate gradient backpropagation	nnd12cg	page 5-19
Marquardt backpropagation	nnd12m	page 5-30
Sample training session	demobp1	page 5-30

Chapter 7: Radial Basis Networks

	Filename	Page
Radial basis approximation	demorb1	page 7-8
Radial basis underlapping neurons	demorb3	page 7-8
Radial basis overlapping neurons	demorb4	page 7-8
GRNN function approximation	demogrn1	page 7-11
PNN classification	demopnn1	page 7-14

Chapter 8: Self-Organizing and Learn. Vector Quant. Nets

	Filename	Page
Competitive learning	democ1	page 8-8
One-dimensional self-organizing map	demosm1	page 8-23
Two-dimensional self-organizing map	demosm2	page 8-23
Learning vector quantization	demolvq1	page 8-38

Chapter 9: Recurrent Networks

	Filename	Page
Hopfield two neuron design	demohop1	page 9-1
Hopfield unstable equilibria	demohop2	page 9-14
Hopfield three neuron design	demohop3	page 9-14
Hopfield spurious stable points	demohop4	page 9-14

Chapter 10: Adaptive Networks

	Filename	Page
Adaptive noise cancellation, toolbox example	demolin8	page 10-16
Adaptive noise cancellation in airplane cockpit	nnd10nc	page 10-14

Chapter 11: Applications

	Filename	Page
Linear design	applin1	page 11-3
Adaptive linear prediction	applin2	page 11-7
Elman amplitude detection	appelm1	page 11-11
Character recognition	appcr1	page 11-16

Bibliography

Simulink

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