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This article will explain in detail what the function of the MATLAB neural network toolbox is, and the content of the article is of high quality, so the editor will share it with you for reference. I hope you will have a certain understanding of the relevant knowledge after reading this article.

Note: the functions listed are applicable to MATLAB5.3 or above, and only the function name is listed for the sake of brevity.

1. Network creation function

Newp creates Perceptron Network

Newlind Design a Linear layer

Newlin creates a linear layer

Newff creates a Feedforward BP Network

Newcf creates a Multi-layer Feedforward BP Network

Newfftd creates a Feedforward input delay BP Network

Designing a Radial basis function Network by newrb

Newrbe designs a strict radial basis network

Newgrnn Design a Generalized regression Neural Network

Newpnn Design a probabilistic Neural Network

Newc creates a competitive layer

Newsom creates a self-organizing feature map

Newhop creates a Hopfield Recursive Network

Newelm creates an Elman Recursive Network

two。 Network application function

Sim simulates a neural network

Init initializes a neural network

Adaptive adapt Neural Network

Train trains a neural network

3. Weight function

Dot product of dotprod weight function

The derivative of the Point Product of ddotprod weight function

Dist Euclidean distance weight function

Normprod gauge point product weight function

Negdist Negative distance weight function

Mandist Manhattan distance weight function

Linkdist Link distance weight function

4. Network input function

Summation of input functions of netsum Network

The derivative of the Sum of input functions of dnetsum Network

5. Transfer function

Hardlim hard limiting transfer function

Hardlims symmetric hard limiting transfer function

Purelin linear transfer function

Tansig tangent S-type transfer function

Logsig logarithmic S-type transfer function

Derivative of dpurelin linear transfer function

The derivative of dtansig Tangent S-type transfer function

The derivative of dlogsig logarithmic S-type transfer function

Compet competitive transfer function

Radbas radial basis transfer function

Satlins symmetric saturated linear transfer function

6. Initialization function

Network initialization function between initlay layer and layer

Initialization function of initwb threshold and weight

Initialization function of zero weight / threshold for initzero

Initialization function of initnw Nguyen_Widrow layer

Initialization function of initcon Conscience threshold

Midpoint midpoint weight initialization function

7. Performance analysis function

Mae mean absolute error performance analysis function

Mse mean square error performance analysis function

Msereg mean square error w/reg performance analysis function

Derivative of dmse mean square error performance analysis function

Derivative of dmsereg mean square error w/reg performance analysis function

8. Learning function

Learnp perceptron learning function

Learnpn standard perceptron learning function

Learnwh Widrow_Hoff learning rules

Learngd BP learning rules

BP Learning rules of learngdm-driven quantitative items

Learnk Kohonen weight learning function

Learncon Conscience threshold learning function

Learnsom self-organizing mapping weight learning function

9. Adaptive function

Adaptive function of weight and threshold of adaptwb Network

10. Training function

Training function of weight and threshold of trainwb Network

Training function of BP algorithm for traingd gradient descent

Training function of BP algorithm for decreasing w / momentum of traingdm gradient

Training function of BP algorithm for traingda gradient descent w / adaptive lr

Training function of BP algorithm for traingdx gradient descent w / momentum and adaptive lr

BP algorithm training function of trainlm Levenberg_Marquardt

Trainwbl uses a training function of a weight vector or a deviation vector per training cycle.

11. Analysis function

The maximum Learning rate of maxlinlr Linear Learning layer

Errsurf error surface

twelve。 Drawing function

Plotes drawing error surface

The position of plotep drawing weight and threshold on the error surface

Drawing self-organizing Map by plotsom

13. Symbolic transformation function

Ind2vec converts subscript to vector

Vec2ind converts a vector to a subscript vector 14. Topological function

Gridtop network layer topology function

Hextop hexagonal layer topology function

Randtop random layer topology function

On the MATLAB neural network toolbox function is shared here, I hope that the above content can be of some help to you, can learn more knowledge. If you think the article is good, you can share it for more people to see.

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