Ch2/Ch2_Perceptron.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def AND(x1, x2):\n",
    "    w1, w2, theta = 0.5, 0.5, 0.7\n",
    "    tmp = x1*w1 + x2*w2\n",
    "    if tmp <= theta:\n",
    "        return 0\n",
    "    elif tmp > theta:\n",
    "        return 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "0\n",
      "0\n",
      "1\n"
     ]
    }
   ],
   "source": [
    "print(AND(0, 0)) # 0을 출력\n",
    "print(AND(1, 0)) # 0을 출력\n",
    "print(AND(0, 1)) # 0을 출력\n",
    "print(AND(1, 1)) # 1을 출력"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def AND(x1, x2):\n",
    "    x = np.array([x1, x2])\n",
    "    w = np.array([0.5, 0.5])\n",
    "    b = -0.7\n",
    "    tmp = np.sum(w*x) + b\n",
    "    if tmp <= 0:\n",
    "        return 0\n",
    "    else:\n",
    "        return 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "0\n",
      "0\n",
      "1\n"
     ]
    }
   ],
   "source": [
    "print(AND(0, 0)) # 0을 출력\n",
    "print(AND(1, 0)) # 0을 출력\n",
    "print(AND(0, 1)) # 0을 출력\n",
    "print(AND(1, 1)) # 1을 출력"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def NAND(x1, x2):\n",
    "    x = np.array([x1, x2])\n",
    "    w = np.array([-0.5, -0.5])\n",
    "    b = 0.7\n",
    "    tmp = np.sum(w*x) + b\n",
    "    if tmp <= 0:\n",
    "        return 0\n",
    "    else:\n",
    "        return 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def OR(x1, x2):\n",
    "    x = np.array([x1, x2])\n",
    "    w = np.array([0.5, 0.5]) # AND와는 가중치(w와 b)만 다르다\n",
    "    b = -0.2\n",
    "    tmp = np.sum(w*x) + b\n",
    "    if tmp <= 0:\n",
    "        return 0\n",
    "    else:\n",
    "        return 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def XOR(x1, x2):\n",
    "    s1 = NAND(x1, x2)\n",
    "    s2 = OR(x1, x2)\n",
    "    y = AND(s1, s2)\n",
    "    return y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "1\n",
      "1\n",
      "0\n"
     ]
    }
   ],
   "source": [
    "print(XOR(0, 0)) # 0을 출력\n",
    "print(XOR(1, 0)) # 1을 출력\n",
    "print(XOR(0, 1)) # 1을 출력\n",
    "print(XOR(1, 1)) # 0을 출력"
   ]
  }
 ],
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