深度学习入门 2 感知机

深度学习入门 基于Python的理论与实现

2 感知机

与门

def AND(x1, x2):
    w1, w2, theta = 0.5, 0.5, 0.7
    tmp = x1*w1 + x2*w2
    if tmp<=theta:
        return 0
    elif tmp>theta:
        return 1

print(AND(0, 0))
print(AND(1, 0))
print(AND(0, 1))
print(AND(1, 1))

与门（用numpy的机制）

import numpy as np

def AND(x1, x2):
    x = np.array([x1, x2])
    w = np.array([0.5, 0.5])
    b = -0.7
    tmp = np.sum(w*x) + b
    if tmp <= 0:
        return 0
    else:
        return 1

print(AND(0, 0))
print(AND(1, 0))
print(AND(0, 1))
print(AND(1, 1))

与非门

def NAND(x1, x2):
    x = np.array([x1, x2])
    w = np.array([-0.5, -0.5])
    b = 0.7
    tmp = np.sum(w*x) + b
    if tmp <= 0:
        return 0
    else:
        return 1

或门

def OR(x1, x2):
    x = np.array([x1, x2])
    w = np.array([0.5, 0.5])
    b = -0.2
    tmp = np.sum(w*x) + b
    if tmp <= 0:
        return 0
    else:
        return 1