A perceptron adds up all the weighted inputs it receives, and if it exceeds a certain value, it outputs a 1, otherwise it just outputs a 0.
a) True
b) False
c) Sometimes – it can also output intermediate values as well
d) Can’t say
What is the difference between a Feedforward Neural Network and Recurrent Neural Network?
Which of the following is true? Single layer associative neural networks do not have the ability to: (i) perform pattern recognition (ii) find the parity of a picture (iii)determine whether two or more shapes in a picture are connected or not a) (ii) and (iii) are true b) (ii) is true c) All of the mentioned d) None of the mentioned
Explain in detail Neural Networks?
What is a neural network and what are some advantages and disadvantages of such a network?
What are the applications of a Recurrent Neural Network (RNN)?
What are neural networks? What are the types of neural networks?
I need a MATLAB source code to recognize different regular geometric shapes such as: squares,rectangles,triangles,circles and ellipses in different sizes using neural network. All of the images containing these shapes should be in binary format with the size of 300*400 pixels. would you please give me a MATLAB code to detect these geometric shapes?
How many kinds of kohonen networks exist?
What learning rate should be used for backprop?
Which is true for neural networks? a) It has set of nodes and connections b) Each node computes it’s weighted input c) Node could be in excited state or non-excited state d) All of the mentioned
What are neural networks and how do they relate to ai?
The network that involves backward links from output to the input and hidden layers is called as ____. a) Self organizing maps b) Perceptrons c) Recurrent neural network d) Multi layered perceptron