Which of the following phenomena can be modeled by unsupervised learning? 84. (part 25, easy) 105-Final
A. The integrator neurons in the oculomotor system.
B. Associative memory.
Classical conditioning.
D. Ocular dominance.
查看答案
In the unsupervised learning described in the part 25, the synaptic weight change is determined by 82. (part 25, difficult) 105-Final
A. the firing rate of the postsynaptic neuron
B. the synaptic normalization
C. the correlation between inputs to different synapses.
D. the external supervised signal that carries the correct responses.
To address the problem of the basic Hebb rule in the firing rate model, several solutions have been proposed. Which of the following concepts is not one of them? 79. (part 24, medium) 105-Final
A. synaptic depression
B. sliding threshold
C. synaptic normalization
D. spike-timing dependent plasticity.
Given the simple firing rate model, τdv/dt=-v+w · u, in which v is the rate of the postsynaptic neuron, u and w are vectors representing the rates of the presynaptic neurons and the corresponding synaptic weights, respectively, which of the following equations describes the basic Hebb learning rule? *77. (part 24, easy) 105-Final
A. τwdw/dt=vu
B. w=vu
C. dw/dt=u
D. u=vw
The long-term synaptic potentiation is specific because 75. (part 23, medium) 105-Final
A. when a neuron is activated by a high frequency input at a specific synapse, all other inactivated synapses also become facilitated.
B. induction of the synaptic potentiation only occurs at the synapses that undergo high frequency stimulations, not at the other inactivated synapses.
C. when a neuron is activated by a high frequency input at a specific synapse, other co-activated synapses also facilitated.
D. only one specific synapse in each neuron can be facilitated.
微信支付 
支付宝支付