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Neural Network Practice Test: Activation and Synaptic Dynamics
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Activation and Synaptic Dynamics topics include: Learning basics and laws, dynamics and activation models, pattern recognition and stability concepts. An Activation Function decides whether a neuron should be activated or not. This means that it will decide whether the neuron's input to the network is important or not in the process of prediction using simpler mathematical operations. Synaptic dynamics describes the time-dependent changes in synaptic currents that alter the strength of coupling between neurons. Various mechanisms, both pre- and postsynaptic, contribute to ongoing changes of... Show more
Neural Network Practice Test: Activation and Synaptic Dynamics
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25 Questions

1. What is nature of input in activation dynamics?
2. Did existence of lyapunov function is necessary for stability?
3. Reinforcement learning is also known as learning with critic?
4. What is hebbian learning?
5. What are the requirements of learning laws?
6. What is asynchronous update in a network?
7. Activation value is associated with?
8. What leads to minimization of error between the desired & actual outputs?
9. Memory decay affects what kind of memory?
10. Convergence refers to equilibrium behaviour of activation state?
11. What is supervised learning?
12. What is unsupervised learning?
13. Whats true for Min-max learning?
14. What kind of dynamics leads to learning laws?
15. In nearest neighbour case, the stored pattern closest to input pattern is recalled, where does it occurs?
16. What is temporal learning?
17. Continuous perceptron learning is also known as delta learning?
18. What is fixed credit assignment?
19. What is differential competitive learning?
20. If weights are not symmetric i.e cik =! cki, then what happens?
21. What is competitive learning?
22. If states of system experience basins of attraction, then system may achieve what kind of stability?
23. Who proposed the shunting activation model?
24. If xb(t) represents differentiation of state x(t), then a stochastic model can be represented by?
25. What does 3rd theorem that describe the stability of a set of nonlinear dynamical systems?