Thesis - Department of Electronic & Computer Engineering

More documents

Recommendations

Info

0.7The average collision rate of the loser0.60.5MeasuredBy Periodic modelBy Poisson modelCollision rate0.40.30.20.100.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4ThresholdFig. 5.14 The collision rate of the loserIt turns out that the periodic model gives better estimations than Poisson model,especially for the winner. The estimations of the winner’s collision rates by the periodicmodel match the measured ones almost perfectly. When the average collision rateis high enough, the estimations of the loser’s collision rate by the periodic model stillgive smaller error than Poisson model. However, when the collision rate is quite small,the estimations by the periodic model have larger error. It must be pointed out that wecare about the collision rate only when the average collision rate is fairly large, otherwisethe performance of the system is no longer governed by the collision rate. For thisreason, the periodic model is better than Poisson model.62
5.7.4 SummaryCompared with the Poisson model, the periodic model tends to reduce the randomness,excluding the collision between two spikes from the same neuron, and it is a bettermodel for collision analysis, especially for small networks or networks containingdifferent populations of neurons.The simulation results shows that the more active the neuron, the lower its collisionrate. In other words, the pulse based communication scheme is in favour of theactive neurons rather than the passive ones, which is the beauty of the AER representationas well, allocating more channel capacity to the more active cells. This phenomenais consistent with the theoretical analysis based on the periodic model.The difference between the two models is remarkable only when the network sizeis small or the neurons can be classified into different populations according to thedegree of neural activity. When the network size is large enough and all the neurons inthe network exhibit similar activities, there is only nuance between them.To scale up the network sizeN, we can simply scale down the pulse widthT pwhile keeping the same collision rate. Thus the same performance can be preserved.T pHowever, is limited by the minimum pulse duration ∆ , which is necessary to generatea suitable spike. Therefore the network size N is limited by ∆ with other conditionsunchanged.As shown, for the given pulse coupled WTA network withN = 10, we can find asuitable threshold to achieve the same competitive behavior ifT p = 0.01. It is reasonableto expect that the same qualitative behavior can be achieved for a network size63
Page 3 and 4:
the system level. Our results show
Page 5:
activities. The basin of attraction
Page 9 and 10:
It is interesting to note that whic
Page 11 and 12: Although there is no saturation in
Page 13 and 14: • Response time of the system;As
Page 15 and 16: e verified by computer simulation (
Page 17 and 18: inhibition. Due to the fact that ea
Page 19 and 20: tion. Thus the power consumption is
Page 21 and 22: Let∆be the minimum time necessary
Page 23 and 24: The sender initiates the sequence b
Page 25 and 26: Here in Table 1 is the comparison o
Page 27 and 28: source cell will be broadcast on th
Page 29 and 30: At this point, it seems appropriate
Page 31 and 32: detected, all the potential spikes
Page 33 and 34: InitializationFor each timestep ε
Page 35 and 36: global inhibition BusActivity to fr
Page 37 and 38: Spikes from the winnerATpTTT n T n+
Page 39 and 40: the network will either work at WTA
Page 41 and 42: The computer simulation results for
Page 43 and 44: 5.5 Steady State AnalysisAs demonst
Page 45 and 46: all the losers. To ensure that all
Page 47 and 48: 10090θ=θ mThe necessary condition
Page 49 and 50: 100Necessary conditions to exhibit
Page 51 and 52: The response time is estimated in t
Page 53 and 54: 5.6.2 Further study on the non-arbi
Page 55 and 56: 100Response time V.S. equivalent ga
Page 57 and 58: cell will never collide with each o
Page 59 and 60: ps ( i) = ( 1 - ϕ i)δ( s)for s =
Page 61: These results show that the collisi
Page 65 and 66: 6. ConclusionsIn this thesis, a cla
Page 67 and 68: In this thesis, we consider only a
Page 69 and 70: v i() t≤I i----------- ( 1 - e1 -
Page 71 and 72: If a+ b - 1≥0, then τ---- d [ v
Page 73 and 74: If a+ b - 1 > 0, since v i() t > 0
Page 75 and 76: whereV ˙ i () t=max( v i ()0 t , )
Page 77 and 78: θ t s Nf f wp ct(%) p cl(%) p cw(%
Page 79 and 80: 10. “WTA networks with lateral ex
show all

Thesis - Department of Electronic & Computer Engineering

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?