About this document
Perceptron Network Training and Applications by John is a document available to read on EtoBox.
The document discusses perceptron networks, including: 1) The perceptron learning rule is more powerful than the Hebb rule and uses an iterative weight adjustment process. 2) The original perceptron has three layers - sensory, associator, and response units. 3) A single layer perceptron consists of a single neuron and is limited to performing pattern classification with only two linearly separable classes. The training continues until no errors occur.
- Author
- John
- Language
- EN