diff --git a/scikits/learn/ann/rbf.py b/scikits/learn/ann/rbf.py
new file mode 100644
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+++ b/scikits/learn/ann/rbf.py
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+# rbf2.py
+# tilde
+# 2006/08/18
+# - new attempt at RBF net to get my ideas straight...deadline is fast approaching!
+
+from numpy import *
+
+class rbf:
+
+    _type = 'rbf'
+    
+    def __init__(nin,nhid,nout,trndata):
+        # set easy params
+        self.nin = nin
+        self.nhid = nhid
+        self.nout = nout
+        # choose subset (1/5?) of training data for basis fxn centers and
+        self.centers = []
+        for i in trndata:
+            if random.random < 0.2:
+                self.centers.append(i)
+        # set common variance proportional to max dist between centers
+        d_max = 0.0
+        for i in self.centers:
+            for j in self.centers:
+                tmp = sqrt((i-j)**2)
+                if tmp > d_max:
+                    d_max = tmp
+        self.variance = d_max/2.0*size(trndata)
+        
+    
+    def fwd(self,inputs):
+        """ Propagate values forward through the net.
+        Inputs:
+                inputs      - vector of input values
+        """
+        z = exp((-1.0/(2*self.variance))*
+        o = dot(z,self.w) + dot(ones((len(z),1)),self.b)
+