The document outlines the architecture and training process of the MADALINE model, which consists of multiple adaptive linear neurons (adalines) operating in parallel with a single output unit. It describes the adjustment of weights during training and the fixed nature of weights connecting the layers, emphasizing that the training duration for MADALINE is significantly longer than that for ADALINE. Additionally, the document touches on implementing XOR logic using the MADALINE structure and the application of the majority vote rule in certain configurations.

1. MADALINE

2. MADALINE
• Multiple Adaptive Linear Neuron Model
• N/W with many Adalines in parallel with a single output unit
• It may use majority vote rule
• The weights that are connected from the Adaline layer to the Madaline layer
are fixed, positive and possess equal values.
• The weights between the input layer and the Adaline layer are adjusted
during the training process.
• The Adaline and Madaline layer neuron have a bias of excitation “1’’
connected to them.
• The training process for a Madaline system is similar to that of an Adaline.

3. ADALINE ARCHITECTURE

4. MADALINE ARCHITECTURE

5. Training Madaline
• In case of training, the weights between the input layer and the
hidden layer are adjusted
• and the weights between the hidden layer and the output layer are
fixed.
• The time taken for the training process in the Madaline network is
very high compared to that of the Adaline network.

6. Flowchart of Madaline Training
• Check in Book

7. Training Algorithm
• In this training algorithm, only the weights between the hidden layer
and the input layer are adjusted, and the weights for the output units
are fixed. The weights v1,v2,…..vm,and the bias b that enter into
output unit Y are determined so that the response of unit Y is 1. Thus,
the weights entering Y unit may be taken as

10. • XOR implementation using MADALINE

12. Final XOR network realized is:

13. NOTE
• Madalines can be formed with the weights on the output unit set to
perform some logic functions.
• If there are only two hidden units present, or if there are more than
two hidden units, then the “majority vote rule’’ function may be used.

14. THANKYOU