Which of the following is not the promise of artificial neural network? a) It can explain result b) It can survive the failure of some nodes c) It has inherent parallelism d) It can handle noise

1 Answers  

---

Describe the structure of artificial neural networks?

0 Answers  

---

The name for the function in question 16 is a) Step function b) Heaviside function c) Logistic function d) Perceptron function

1 Answers  

---

Neural Networks are complex ______________ with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions

1 Answers  

---

 What is back propagation? a) It is another name given to the curvy function in the perceptron b) It is the transmission of error back through the network to adjust the inputs c) It is the transmission of error back through the network to allow weights to be adjusted so that the network can learn. d) None of the mentioned

1 Answers  

---

What is a Neural Network?

0 Answers  

---

Why use artificial neural networks? What are its advantages?

0 Answers  

---

What are conjugate gradients, levenberg-marquardt, etc.?

0 Answers  

---

What are batch, incremental, on-line, off-line, deterministic, stochastic, adaptive, instantaneous, pattern, constructive, and sequential learning?

0 Answers  

---

 Which of the following is true for neural networks? (i) The training time depends on the size of the network. (ii) Neural networks can be simulated on a conventional computer. (iii) Artificial neurons are identical in operation to biological ones. a) All of the mentioned b) (ii) is true c) (i) and (ii) are true d) None of the mentioned

1 Answers  

---

How neural networks became a universal function approximators?

0 Answers  

---

What are the disadvantages of artificial neural networks?

0 Answers  

---