Nothing

```
norm.sim.ksc.center.update <-
function(mem,A,k,cur.center=NULL){
## A: n by p matrix, each row is a sample
## mem: n by 1, Membership for each sample
## k: the number of clusters
## cur.center: k by p, current cluster centeroids
n = nrow(A); p = ncol(A); new.center = matrix(0,k,p)
for (i in 1:k){
if (sum(mem==i)==0){
new.center[i,] = rep(0,p) ## if the cluster has no members, set the cluster center as zero.
} else {
b = matrix(A[mem==i,],ncol=p)
#M = t(b)%*%b - dim(b)[1]*diag(p)
#ks = eigen(M)$vectors[,1]
#if (sum(ks)<0) ks = -ks
#new.center[i,] = ks
tmp = apply(b,2,mean)
new.center[i,] = tmp/sqrt(sum(tmp^2))
}
}
new.center
}
```

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