Funktionsannäherung und nichtlineare Regression

Erstellen eines neuronalen Netzes zur Verallgemeinerung nichtlinearer Beziehungen zwischen Beispieleingaben und -ausgaben

Apps

Lösung des Anpassungsproblems mit zweischichtigen Feed-Forward-Netzen

`nftool`	Öffnen der App „Neural Net Fitting (Neuronale Netzanpassung)“
`view`	Anzeigen eines flachen neuronalen Netzes

`fitnet`	Neuronales Netz zur Funktionsanpassung
`feedforwardnet`	Erstellen eines neuronalen Feedforward-Netzes
`cascadeforwardnet`	Generieren von vorwärtsgerichteten Kaskadennetzen

`train`	Trainieren von flachen neuronalen Netzen
`trainlm`	Levenberg-Marquardt backpropagation
`trainbr`	Bayesian regularization backpropagation
`trainscg`	Scaled conjugate gradient backpropagation
`trainrp`	Resilient backpropagation
`mse`	Leistungsfunktion der mittleren quadratischen Abweichung
`regression`	(Nicht empfohlen) Durchführen einer linearen Regression flacher Netzausgänge an Zielen
`ploterrhist`	Plot error histogram
`plotfit`	Darstellen der Funktionsanpassung
`plotperform`	Plot network performance
`plotregression`	Plotten von linearer Regression
`plottrainstate`	Plotten von Trainingszustandswerten
`genFunction`	Generate MATLAB function for simulating shallow neural network

Flache Netze für Mustererkennung, Clustering und Zeitreihen
Verwendung von Apps und Funktionen zum Entwickeln flacher neuronaler Netze für Funktionsanpassung, Mustererkennung, Clustering und Zeitreihenanalyse.
Anpassen von Daten mit einem flachen neuronalen Netz
Trainieren eines flachen neuronalen Netzes zum Anpassen eines Datensatzes.
Create, Configure, and Initialize Multilayer Shallow Neural Networks
Prepare a multilayer shallow neural network.
Body Fat Estimation
This example illustrates how a function fitting neural network can estimate body fat percentage based on anatomical measurements.
Train and Apply Multilayer Shallow Neural Networks
Train and use a multilayer shallow network for function approximation or pattern recognition.
Analyze Shallow Neural Network Performance After Training
Analyze network performance and adjust training process, network architecture, or data.
Deploy Shallow Neural Network Functions
Simulate and deploy trained shallow neural networks using MATLAB^® tools.
Deploy Training of Shallow Neural Networks
Learn how to deploy training of shallow neural networks.

Shallow Neural Networks with Parallel and GPU Computing
Use parallel and distributed computing to speed up neural network training and simulation and handle large data.
Automatically Save Checkpoints During Neural Network Training
Save intermediate results to protect the value of long training runs.
Optimize Neural Network Training Speed and Memory
Make neural network training more efficient.
Trainieren von flachen Netzen mit Prozessoren und Grafikkarten
Schnelleres Training und schnellere Simulation großer Probleme mithilfe flacher Netze.

Choose Neural Network Input-Output Processing Functions
Preprocess inputs and targets for more efficient training.
Configure Shallow Neural Network Inputs and Outputs
Learn how to manually configure the network before training using the configure function.
Divide Data for Optimal Neural Network Training
Use functions to divide the data into training, validation, and test sets.
Choose a Multilayer Neural Network Training Function
Comparison of training algorithms on different problem types.
Improve Shallow Neural Network Generalization and Avoid Overfitting
Learn methods to improve generalization and prevent overfitting.
Train Neural Networks with Error Weights
Learn how to use error weighting when training neural networks.
Normalize Errors of Multiple Outputs
Learn how to fit output elements with different ranges of values.

Workflow for Neural Network Design
Learn the primary steps in a neural network design process.
Four Levels of Neural Network Design
Learn the different levels of using neural network functionality.
Mehrschichtige flache neuronale Netze und Backpropagationstraining
Workflow zur Entwicklung eines mehrschichtigen, flachen neuronalen Feed-Forward-Netzes für die Funktionsanpassung und Mustererkennung.
Multilayer Shallow Neural Network Architecture
Learn the architecture of a multilayer shallow neural network.
Understanding Shallow Network Data Structures
Learn how the format of input data structures affects the simulation of networks.
Beispieldatensätze für flache neuronale Netze
Liste der Beispieldatensätze, die zum Experimentieren mit flachen neuronalen Netzen verwendet werden können.
Neural Network Object Properties
Learn properties that define the basic features of a network.
Neural Network Subobject Properties
Learn properties that define network details such as inputs, layers, outputs, targets, biases, and weights.