Manhattan distance weight function
Z = mandist(W,P)
D = mandist(pos)
mandist
is the Manhattan distance weight
function. Weight functions apply weights to an input to get weighted
inputs.
Z = mandist(W,P)
takes these inputs,
W 

P 

and returns the S
byQ
matrix
of vector distances.
mandist
is also a layer distance function,
which can be used to find the distances between neurons in a layer.
D = mandist(pos)
takes one argument,
pos 

and returns the S
byS
matrix
of distances.
Here you define a random weight matrix W
and
input vector P
and calculate the corresponding
weighted input Z
.
W = rand(4,3); P = rand(3,1); Z = mandist(W,P)
Here you define a random matrix of positions for 10 neurons arranged in threedimensional space and then find their distances.
pos = rand(3,10); D = mandist(pos)
To change a network so an input weight uses mandist
,
set net.inputWeights{i,j}.weightFcn
to 'mandist'
.
For a layer weight, set net.layerWeights{i,j}.weightFcn
to 'mandist'
.
To change a network so a layer's topology uses mandist
,
set net.layers{i}.distanceFcn
to 'mandist'
.
In either case, call sim
to simulate the
network with dist
. See newpnn
or newgrnn
for simulation examples.