A Simple FeedForward Three Input Perceptron(Neural Network) using C#

Simple Perceptron with binary classifier using C#

The following code is a simple three input perceptron neural network with a binary classifier using c#.
This neural net was the most primitive invented by Rosenblatt in 1959.

// A simple three input Perceptron Model using C#

using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;

namespace ConsoleApplication1
{
    class perceptrontest1
    {
        static void elements()
        {
            //intialization of inputs and weights for nueral net//

            decimal x1, x2, x3, w1, w2, w3;
            decimal isum,thresh;
            // bias input to neural net//
            int bias=1;
            // Provide userdefined inputs and weights//
            Console.WriteLine("enter the inputs to be feeded in perceptron");
            x1 = Convert.ToDecimal(Console.ReadLine());
            x2 = Convert.ToDecimal(Console.ReadLine());
            x3 = Convert.ToDecimal(Console.ReadLine());
            Console.WriteLine("enter the value of the weights");
            w1 = Convert.ToDecimal(Console.ReadLine());
            w2 = Convert.ToDecimal(Console.ReadLine());
            w3 = Convert.ToDecimal(Console.ReadLine());
            // calculation of sum//
            Console.WriteLine("calculating");
            isum = (x1 * w1 + x2 * w2 + x3 * w3)+bias;
            Console.WriteLine("The summed output is:{0} ",isum);
            Console.WriteLine("enter the desired threshold value");
            thresh = Convert.ToDecimal(Console.ReadLine());
           
            // Binary classifier//

            if (isum > thresh)
            {
                int y = 0;
                Console.WriteLine("your classification is:{0}",y);
            }
            else if (isum < thresh)
            {
                int y = 1;
                Console.WriteLine("your classification is:{0}",y);
            }
           
        }
        static void Main(string[] args)
        {
            elements();
        }
    }
}