MCQOPTIONS
Saved Bookmarks
MCQOPTIONS
This section includes 12 Mcqs, each offering curated multiple-choice questions to sharpen your Neural Networks knowledge and support exam preparation. Choose a topic below to get started.
| 1. |
The update in weight vector in basic competitive learning can be represented by? |
| A. | w(t + 1) = w(t) + del.w(t) |
| B. | w(t + 1) = w(t) |
| C. | w(t + 1) = w(t) – del.w(t) |
| D. | none of the mentioned |
| Answer» B. w(t + 1) = w(t) | |
| 2. |
How is weight vector adjusted in basic competitive learning?a) such that it moves towards the input vectorb) such that it moves away from input vector |
| A. | such that it moves towards the input vectorb) such that it moves away from input vectora) such that it moves towards the output vector |
| B. | such that it moves away from input vectora) such that it moves towards the output vectorb) such that it moves away from output vector |
| Answer» B. such that it moves away from input vectora) such that it moves towards the output vectorb) such that it moves away from output vector | |
| 3. |
What conditions are must for competitive network to perform feature mapping? |
| A. | non linear output layers |
| B. | connection to neighbours is excitatory and to the farther units inhibitory |
| C. | on centre off surround connections |
| D. | none of the mentioned fulfils the whole criteria |
| Answer» E. | |
| 4. |
HOW_IS_WEIGHT_VECTOR_ADJUSTED_IN_BASIC_COMPETITIVE_LEARNING??$ |
| A. | such that it moves towards the input vector |
| B. | such that it moves away from input vector |
| C. | such that it moves towards the output vector |
| D. | such that it moves away from output vector |
| Answer» B. such that it moves away from input vector | |
| 5. |
The_update_in_weight_vector_in_basic_competitive_learning_can_be_represented_by?$ |
| A. | w(t + 1) = w(t) + del.w(t) |
| B. | w(t + 1) = w(t) |
| C. | w(t + 1) = w(t) – del.w(t) |
| D. | none of the mentioned |
| Answer» B. w(t + 1) = w(t) | |
| 6. |
What is an instar? |
| A. | receives inputs from all others |
| B. | gives output to all others |
| C. | may receive or give input or output to others |
| D. | none of the mentioned |
| Answer» B. gives output to all others | |
| 7. |
If a competitive network can perform feature mapping then what is that network can be called? |
| A. | self excitatory |
| B. | self inhibitory |
| C. | self organization |
| D. | none of the mentioned |
| Answer» D. none of the mentioned | |
| 8. |
What conditions are must for competitive network to perform pattern clustering? |
| A. | non linear output layers |
| B. | connection to neighbours is excitatory and to the farther units inhibitory |
| C. | on centre off surround connections |
| D. | none of the mentioned fulfils the whole criteria |
| Answer» E. | |
| 9. |
What consist of competitive learning neural networks? |
| A. | feedforward paths |
| B. | feedback paths |
| C. | either feedforward or feedback |
| D. | combination of feedforward and feedback |
| Answer» D. combination of feedforward and feedback | |
| 10. |
What is the nature of general feedback given in competitive neural networks? |
| A. | self excitatory |
| B. | self inhibitory |
| C. | self excitatory or self inhibitory |
| D. | none of the mentioned |
| Answer» B. self inhibitory | |
| 11. |
Which layer has feedback weights in competitive neural networks? |
| A. | input layer |
| B. | second layer |
| C. | both input and second layer |
| D. | none of the mentioned |
| Answer» C. both input and second layer | |
| 12. |
How are input layer units connected to second layer in competitive learning networks? |
| A. | feedforward manner |
| B. | feedback manner |
| C. | feedforward and feedback |
| D. | feedforward or feedback |
| Answer» B. feedback manner | |