What is full counter propagation network?

Full counterpropagation network: The vector x and y propagate through the network in a counterflow manner to yield output vector x* and y*. Architecture of Full CPN: The four major components of the instar-outstar model are the input layer, the instar, the competitive layer and the outstar.

What type of learning is normally used to train the Outstar weights of a Counterpropagation network?

Fuzzy Competitive Learning
In this process, the weight connecting between the instar and outstar, that is, input-hidden and hidden-output layer, respectively, is adjusted by using Fuzzy Competitive Learning (FCL).

What consists of a basic counter propagation network?

9. What consist of a basic counterpropagation network? Explanation: Counterpropagation network consist of two feedforward network with a common hidden layer.

What is an auto associative network?

Autoassociative neural networks are feedforward nets trained to produce an approximation of the identity mapping between network inputs and outputs using backpropagation or similar learning procedures. The key feature of an autoassociative network is a dimensional bottleneck between input and output.

Which is the most direct application of neural networks?

Explanation: Wall folloing is a simple task and doesn’t require any feedback. 2. Which is the most direct application of neural networks? Explanation: Its is the most direct and multilayer feedforward networks became popular because of this.

What is the architecture of back propagation network?

A back propagation neural network is a multilayer, feed-forward neural network consisting of an input layer, hidden layer and an output layer. The neurons present in the hidden and output layers have biases, which are the connections from the units whose activation is always 1.

What type learning is involved in art?

unsupervised learning
6. hat type learning is involved in ART? Explanation: CPN is a unsupervised learning.

What is Hopfield network in soft computing?

Hopfield network is a special kind of neural network whose response is different from other neural networks. It is calculated by converging iterative process. It has just one layer of neurons relating to the size of the input and output, which must be the same.

How does the name counter propagation significant its architecture?

To elaborate: Counterpropagation network has ability to learn forward and inverse mapping functions.

Does Max pooling always decrease parameters?

20) In CNN, having max pooling always decrease the parameters? This is not always true. If we have a max pooling layer of pooling size as 1, the parameters would remain the same. BackPropogation can be applied on pooling layers too.

What is AI Mcq?

Making a machine Intelligent. Explanation: Artificial Intelligence is a branch of Computer science, which aims to create intelligent machines so that machine can think intelligently in the same manner as a human does.

Which learning is better for pattern association?

Explanation: Competitive learning net is used for pattern grouping.