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39 changes: 39 additions & 0 deletions Neural Networks/src/delta_learning.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,39 @@
from math import exp


def mul(l1, l2):
return round(sum(a*b for a,b in zip(l1, l2)), 3)

def sgn(x):
return 1 if x > 0 else -1
def imul(x, a):
return [round(a*xi,3) for xi in x]
def add(l1, l2):
return [round(a+b,3) for a,b in zip(l1, l2)]
def func(net):
# bipolar continuous
return 2 / (1 + exp(-net)) - 1
def funcdash(o):
return (1 - o*o)/2

if __name__ == '__main__':
c = 0.1
n = int(input('Enter no of input:'))
xn, dn = [], []
for i in range(n):
xi = list(map(float, input(f'Enter x{i}: ').strip().split(' ')))
di = int(input('Enter desired output:'))
xn.append(xi); dn.append(di)
w = list(map(float, input('Enter initial weights:').split(' ')))
for xi, di in zip(xn, dn):
# print(f'Input: {xi}')
net = mul(w, xi)
# print(f'Expected output: {di}, Actual output: {net}')

oi = round(func(net), 3)
fnetdash = round(funcdash(oi), 3)
print(f'oi = {oi}, fnetdash = {fnetdash}')

xi = imul(xi, c * (di - oi) * fnetdash)
w = add(w, xi)
print(f'Updated weight: {w}')
39 changes: 39 additions & 0 deletions Neural Networks/src/perceptron_learning.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,39 @@
import math


def sgn(x):
return 1 if x>0 else -1

def add(a, b):
return [round(ai+bi, 2) for ai, bi in zip(a, b)]

def var_mul(x, a):
return [round(x*ai, 2) for ai in a]

def mult(a, b):
return sum([ai*bi for ai, bi in zip(a, b)])

if __name__ == '__main__':
c = 0.1
n = int(input('Enter no of input:'))
x, d = [],[]
for i in range(n):
xi = list(map(float, input(f'Enter x{i}: ').strip().split(' ')))
di = int(input('Enter desired output:'))
x.append(xi); d.append(di)

w = list(map(float, input('Enter initial weights:').split(' ')))


for xi, di in zip(x, d):
net = mult(xi, w)
if(sgn(net) != sgn(di)):
print("Correction Needed...")
w = add(w, var_mul(c*(di - sgn(net)), xi))
print("X: ", xi)
print(f"W: {w}\n")
else:
print("Correction Not Needed..")
print("X: ", xi)
print(f"W: {w}\n")
continue