Neural Network Toolbox

Reference


Function and type
`assoclr`	Associative learning rules
`backprop`	Backpropagation networks
`elman`	Elman recurrent networks
`hopfield`	Hopfield recurrent networks
`linnet`	Linear networks
`lvq`	Learning vector quantization
`percept`	Perceptrons
`radbasis`	Radial basis networks
`selforg`	Self-organizing networks

Functions by Class


Adapt Function
`adaptwb`	By-weight-and-bias network adaption function.


Analysis Functions
`errsurf`	Error surface of a single input neuron.
`maxlinr`	Maximum learning rate for a linear neuron.


Distance Functions
`boxdist`	Distance between two position vectors
`dist`	Euclidean distance weight function.
`linkdist`	Link distance function.
`mandist`	Manhattan distance weight function.


Layer Initialization Functions
`initnw`	Nguyen-Widrow layer initialization function.
`initwb`	By-weight-and-bias layer initialization function


Learning Functions
`learncon`	Conscience bias learning function.
`learngd`	Gradient descent weight/bias learning function
`learngdm`	Grad. descent w/momentum weight/bias learning function
`learnh`	Hebb weight learning function.
`learnhd`	Hebb with decay weight learning function.
`learnis`	Instar weight learning function.
`learnk`	Kohonen weight learning function.
`learnlv1`	LVQ1 weight learning function.
`learnlv2`	LVQ2 weight learning function.
`learnos`	Outstar weight learning function.
`learnp`	Perceptron weight/bias learning function.
`learnpn`	Normalized perceptron weight/bias learning function.
`learnsom`	Self-organizing map weight learning function.
`learnwh`	Widrow-Hoff weight/bias learning rule

Line Search Functions

srchbac
Backtracking search.

srchbre
Brent's combination golden section/quadratic interpolation.

srchcha
Charalambous' cubic interpolation.

srchgol
Golden section search.

srchhyb
Hybrid bisection/cubic search.

Line Search Functions
`srchbac`	Backtracking search.
`srchbre`	Brent's combination golden section/quadratic interpolation.
`srchcha`	Charalambous' cubic interpolation.
`srchgol`	Golden section search.
`srchhyb`	Hybrid bisection/cubic search.


Net Input Derivative Functions
`dnetprod`	Product net input derivative function.
`dnetsum`	Sum net input derivative function.

Net Input Functions

netprod
Product net input function.

netsum
Sum net input function.

Net Input Functions
`netprod`	Product net input function.
`netsum`	Sum net input function.


Network Initialization Functions
`initlay`	Layer-by-layer network initialization function.


Network Use
`sim`	Simulate a neural network.
`init`	Initialize a neural network.
`adapt`	Allow a neural network to adapt.
`train`	Train a neural network.
`disp`	Display a neural network's properties.
`display`	Display a neural network variable's name and properties.


New Networks
`network`	Create a custom neural network.
`newc`	Create a competitive layer.
`newcf`	Create a cascade-forward backpropagation network.
`newelm`	Create an Elman backpropagation network.
`newff`	Create a feed-forward backpropagation network.
`newfftd`	Create a feed-forward input-delay backprop network.
`newgrnn`	Design a generalized regression neural network.
`newhop`	Create a Hopfield recurrent network.
`newlin`	Create a linear layer.
`newlind`	Design a linear layer.
`newlvq`	Create a learning vector quantization network
`newp`	Create a perceptron.
`newpnn`	Design a probabilistic neural network.
`newrb`	Design a radial basis network.
`newrbe`	Design an exact radial basis network.
`newsom`	Create a self-organizing map.

Performance Derivative Functions

dmae
Mean absolute error performance derivatives function.

dmse
Mean squared error performance derivatives function.

dmsereg
Mean squared error w/reg performance derivative function.

dsse
Sum squared error performance derivative function.

Performance Derivative Functions
`dmae`	Mean absolute error performance derivatives function.
`dmse`	Mean squared error performance derivatives function.
`dmsereg`	Mean squared error w/reg performance derivative function.
`dsse`	Sum squared error performance derivative function.


Performance Functions
`mae`	Mean absolute error performance function.
`mse`	Mean squared error performance function.
`msereg`	Mean squared error w/reg performance function.
`sse`	Sum squared error performance function.

Plotting Functions

hinton
Hinton graph of weight matrix.

hintonwb
Hinton graph of weight matrix and bias vector.

plotep
Plot weight and bias position on error surface.

plotes
Plot error surface of single input neuron.

plotpc
Plot classification line on perceptron vector plot.

plotperf
Plot network performance.

plotpv
Plot perceptron input/target vectors.

plotsom
Plot self-organizing map.

plotv
Plot vectors as lines from the origin.

plotvec
Plot vectors with different colors.

Plotting Functions
`hinton`	Hinton graph of weight matrix.
`hintonwb`	Hinton graph of weight matrix and bias vector.
`plotep`	Plot weight and bias position on error surface.
`plotes`	Plot error surface of single input neuron.
`plotpc`	Plot classification line on perceptron vector plot.
`plotperf`	Plot network performance.
`plotpv`	Plot perceptron input/target vectors.
`plotsom`	Plot self-organizing map.
`plotv`	Plot vectors as lines from the origin.
`plotvec`	Plot vectors with different colors.


Pre and Post Processing
`postmnmx`	Unnormalize data which has been norm. by PREMNMX.
`postreg`	Post-training regression analysis.
`poststd`	Unnormalize data which has been normalized by PRESTD.
`premnmx`	Normalize data for maximum of 1 and minimum of -1.
`prepca`	Principal component analysis on input data.
`prestd`	Normalize data for unity standard deviation and zero mean.
`tramnmx`	Transform data with precalculated minimum and max.
`trapca`	Transform data with PCA matrix computed by PREPCA.
`trastd`	Transform data with precalc. mean & standard deviation.

Simulink Support

gensim
Generate a Simulink block for neural network simulation.

Simulink Support
`gensim`	Generate a Simulink block for neural network simulation.


Topology Functions
`gridtop`	Gridtop layer topology function.
`hextop`	Hexagonal layer topology function.
`randtop`	Random layer topology function.


Training Functions
`trainbfg`	BFGS quasi-Newton backpropagation.
`trainbr`	Bayesian regularization.
`traincgb`	Powell-Beale conjugate gradient backpropagation.
`traincgf`	Fletcher-Powell conjugate gradient backpropagation.
`traincgp`	Polak-Ribiere conjugate gradient backpropagation.
`traingd`	Gradient descent backpropagation.
`traingda`	Gradient descent w/adaptive lr backpropagation.
`traingdm`	Gradient descent w/momentum backpropagation.
`traingdx`	Gradient descent w/momentum & adaptive lr backprop.
`trainlm`	Levenberg-Marquardt backpropagation.
`trainoss`	One step secant backpropagation.
`trainrp`	Resilient backpropagation (Rprop)
`trainscg`	Scaled conjugate gradient backpropagation.
`trainwb`	By-weight-and-bias network training function.
`trainwb1`	By-weight-&-bias 1-vector-at-a-time training function.


Transfer Derivative Functions
`dhardlim`	Hard limit transfer derivative function.
`dhardlms`	Symmetric hard limit transfer derivative function.
`dlogsig`	Log sigmoid transfer derivative function.
`dposlin`	Positive linear transfer derivative function.
`dpurelin`	Hard limit transfer derivative function.
`dradbas`	Radial basis transfer derivative function.
`dsatlin`	Saturating linear transfer derivative function.
`dsatlins`	Symmetric saturating linear transfer derivative function.
`dtansig`	Hyperbolic tangent sigmoid transfer derivative function.
`dtribas`	Triangular basis transfer derivative function

Transfer Functions

compet
Competitive transfer function.

hardlim
Hard limit transfer function.

hardlims
Symmetric hard limit transfer function.

logsig
Log sigmoid transfer function.

poslin
Positive linear transfer function.

purelin
Hard limit transfer function.

radbas
Radial basis transfer function.

satlin
Saturating linear transfer function.

satlins
Symmetric saturating linear transfer function.

softmax
Soft max transfer function.

tansig
Hyperbolic tangent sigmoid transfer function.

tribas
Triangular basis transfer function

Transfer Functions
`compet`	Competitive transfer function.
`hardlim`	Hard limit transfer function.
`hardlims`	Symmetric hard limit transfer function.
`logsig`	Log sigmoid transfer function.
`poslin`	Positive linear transfer function.
`purelin`	Hard limit transfer function.
`radbas`	Radial basis transfer function.
`satlin`	Saturating linear transfer function.
`satlins`	Symmetric saturating linear transfer function.
`softmax`	Soft max transfer function.
`tansig`	Hyperbolic tangent sigmoid transfer function.
`tribas`	Triangular basis transfer function


Vectors
`cell2mat`	Combines cell array of matrices into one matrix.
`combvec`	Create all combinations of vectors.
`concur`	Create concurrent bias vectors.
`con2seq`	Converts concurrent vectors to sequential vectors.
`copy`	Copy matrix or cell array.
`ind2vec`	Convert indices to vectors.
`mat2cell`	Break matrix up into cell array of matrices.
`minmax`	Ranges of matrix rows.
`normc`	Normalize columns of matrix.
`normr`	Normalize rows of matrix.
`pnormc`	Pseudo-normalize columns of matrix.
`quant`	Discretize value as multiple of a quantity.
`seq2con`	Converts sequential vectors to concurrent vectors.
`sumsqr`	Sum squared elements of matrix.
`vec2ind`	Convert vectors to indices.

Weight and Bias Initialization Functions

initcon
Conscience bias initialization function.

initzero
Zero weight/bias initialization function.

midpoint
Midpoint weight initialization function.

randnc
Normalized column weight initialization function.

randnr
Normalized row weight initialization function.

rands
Symmetric random weight/bias initialization function.

Weight and Bias Initialization Functions
`initcon`	Conscience bias initialization function.
`initzero`	Zero weight/bias initialization function.
`midpoint`	Midpoint weight initialization function.
`randnc`	Normalized column weight initialization function.
`randnr`	Normalized row weight initialization function.
`rands`	Symmetric random weight/bias initialization function.


Weight Derivative Functions
`ddotprod`	Dot product weight derivative function.

Weight Functions

dist
Euclidean distance weight function.

dotprod
Dot product weight function.

mandist
Manhattan distance weight function.

negdist
Dot product weight function.

normprod
Normalized dot product weight function.

Weight Functions
`dist`	Euclidean distance weight function.
`dotprod`	Dot product weight function.
`mandist`	Manhattan distance weight function.
`negdist`	Dot product weight function.
`normprod`	Normalized dot product weight function.

Transfer Functions


Transfer Function
`compet`	Competitive transfer function.
`hardlim`	Hard limit transfer function.
`hardlims`	Symmetric hard limit transfer function
`logsig`	Log sigmoid transfer function.
`poslin`	Positive linear transfer function
`purelin`	Linear transfer function.
`radbas`	Radial basis transfer function.
`satlin`	Saturating linear transfer function.
`satlins`	Symmetric saturating linear transfer function
`softmax`	Soft max transfer function.
`tansig`	Hyperbolic tangent sigmoid transfer function.
`tribas`	Triangular basis transfer function.

Transfer Function Graphs

Transfer Function Graphs (continued)

Reference Page Headings

Following is a list of headings used in this section. Not every function will have all this material, but the material that is included will be ordered as shown.

Purpose
Graph and
Symbol
Syntax
To Get Help
Description
Properties
Examples
Network Use
Algorithm
Limitations
Notes
See Also
References

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