Neural Network Toolbox

Working with Neural Network Toolbox

Like its counterpart in the biological nervous system, a neural network can learn and therefore can be trained to find solutions, recognize patterns, classify data, and forecast future events. The behavior of a neural network is defined by the way its individual computing elements are connected and by the strength of those connections, or weights. The weights are automatically adjusted by training the network according to a specified learning rule until it performs the desired task correctly.

Neural Network Toolbox includes command-line functions and graphical tools for creating, training, and simulating neural networks. Graphical tools make it easy to develop neural networks for tasks such as data fitting (including time-series data), pattern recognition, and clustering. After creating your networks in these tools, you can automatically generate MATLAB^® code to capture your work and automate tasks.

The Neural Network Fitting Tool (top) and a performance plot (bottom). The Neural Network Fitting Tool guides you through the process of fitting data using neural networks.