artificial neural network models of real neural computation
DESCRIPTION
Artificial Neural Network Models of Real Neural Computation. Minus times Minus equals Plus: The reason for this we need not discuss. W.H. Auden. 1.0. w 0. p 1. w 1. p 2. w 2. a. p n. w n. p i. Outputs. Inputs. p i. p i. Hidden Units. Training set:. Minimize error. - PowerPoint PPT PresentationTRANSCRIPT
Artificial Neural Network Models of Real Neural Computation
Minus times Minus equals Plus:The reason for this we need not discuss.
W.H. Auden
f ( net ) =
11+e−net
: 'logistic'
w1
w2
w0
wn
.
.
.
1.0
p1
pn
p2 a net =w0 + p1w1 + p2w2 +K + pnwn
a = f (net)
pi
pi
pi
Inputs Outputs
a1
a2
a3
Hidden Units
Training set:
p1 → a*1
M
pi → a* i
M
Error = a
j* i −aj( )
j∑
2
Minimize error
f net( ) =net : 'linear'
Retinal Receptive Field of spatially tuned neuron in area 7a
Experiment
Model
Experiment Model Hidden Units
ExternalInputs
outputs
ExternalInput
Weights
RecurrentWeights
1.0 p1 p2
Non-Zero Weight
<-<-<- Training data
Performance
