Function Approximation and Clustering - MATLAB & Simulink (original) (raw)

Main Content

Perform regression, classification, and clustering using shallow neural networks

Generalize nonlinear relationships between example inputs and outputs, perform unsupervised learning with clustering and autoencoders.

Categories

• Function Approximation and Nonlinear Regression
  Create a neural network to generalize nonlinear relationships between example inputs and outputs
• Pattern Recognition
  Train a neural network to generalize from example inputs and their classes, train autoencoders
• Clustering
  Discover natural distributions, categories, and category relationships
• Autoencoders
  Perform unsupervised learning of features using autoencoder neural networks
• Define Shallow Neural Network Architectures
  Define shallow neural network architectures and algorithms