Unformatted text preview: Lateral inhibitions are realized by the lateral connections from other neurons in the same layer. x i = i th input signal w ji = synaptic weight from input i to neuron j v j = net activity level of neuron j y j = ϕ ( v j ) Fig. 1 Initial output y = [ y 1 y 2 y 3 ] = [0 0 0] Initial weight = 25 . 25 . 25 . 25 . 5 . 5 . 25 . 75 . W y j = ( v j )= + neurons other for neuron winning for 1 = 0.6 Find the synaptic weights after two iterations for the following 2 cases. (a) Initial input x = [ x 1 x 2 x 3 x 4 ] = [1 0 0 0] , (b) Initial input x = [ x 1 x 2 x 3 x 4 ] = [0.4 0.1 0.4 0.1] w 34 w 14 w 24 x 4 x 3 x 2 x 1 w 31 w 21 w 11 y 1 y 2 ν 2 1 y 3 3...
View
Full Document
 Spring '10
 wong
 Synaptic plasticity, competitive learning, constant input signal

Click to edit the document details