def fuzzyAsynMemTriangle(name):
g = NodeGroup("AsynFuzzyMemTriangle", True);
g.addNode(ftriangle,"AsynFuzzyMemTriangle","java");
module = AsynNeuralModule(name+'_AsynFuzzyMemTriangle', g)
module.createEncoder("logic/gates/ina", "float", 1) # x
module.createEncoder("logic/gates/confa", "float", 1) # alpha
module.createEncoder("logic/gates/confb", "float", 1) # beta
module.createEncoder("logic/gates/confc", "float", 1) # gamma
module.createDecoder("logic/gates/outa", "float", 1) # y
return module
def fuzzyAsynMemTriangle(name):
g = NodeGroup("AsynFuzzyMemTriangle", True)
g.addNode(ftriangle, "AsynFuzzyMemTriangle", "java")
module = AsynNeuralModule(name + '_AsynFuzzyMemTriangle', g)
module.createEncoder("logic/gates/ina", "float", 1) # x
module.createEncoder("logic/gates/confa", "float", 1) # alpha
module.createEncoder("logic/gates/confb", "float", 1) # beta
module.createEncoder("logic/gates/confc", "float", 1) # gamma
module.createDecoder("logic/gates/outa", "float", 1) # y
return module
def make(net,name='NeuralModule which implements FuzzyMembership function - Triangular - projectTemplate',
independent=True, useQuick=True):
finder = "org.hanns.myPackage.fuzzy.membership.impl.Triangular";
# create group with a name
g = NodeGroup(name, independent);
g.addNode(finder, "temp_FuzzyMemTriangular", "java");
neuron = NeuralModule(name+"_temp_FuzzyMemTriangular", g)
neuron.createEncoder("logic/gates/ina", "float",1) # termination = data input x
neuron.createEncoder("logic/gates/confa", "float",1) # termination - config input alpha
neuron.createEncoder("logic/gates/confb", "float",1) # termination - config input betaa
neuron.createEncoder("logic/gates/confc", "float",1) # termination - config input gamma
neuron.createDecoder("logic/gates/outa", "float",1) # origin = output of neuron = data output y
many=net.add(neuron) # add it into the network
