Posted on May 15th, 2009 At 2:58 am by baldo
Prerequisites
Hopfield Neural Network able to recall patterns
The g++ version I have used to code this Network is:
$ g++ --version
g++ (Debian 4.3.2-1.1) 4.3.2
Copyright (C) 2008 Free Software Foundation, Inc.
This is free software; see the source for copying conditions. There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
Compiling the Network
$ g++ main.cpp -o hopfield
Running the Network
$ ./hopfield
*******************************
Hopfield Neural Network
able to recall binary patterns
*******************************
Presenting pattern A
component = 1 output = 1 component matched
component = 0 output = 0 component matched
component = 1 output = 1 component matched
component = 0 output = 0 component matched
* Pattern A recalled correctly
Presenting pattern B
component = 0 output = 0 component matched
component = 1 output = 1 component matched
component = 0 output = 0 component matched
component = 1 output = 1 component matched
* Pattern B recalled correctly
Try to modify the input patterns, for example by presenting a pattern like B = {0, 1, 0, 0}, the output would be like this:
.
.
Presenting pattern B
component = 0 output = 0 component matched
component = 1 output = 1 component matched
component = 0 output = 0 component matched
component = 0 output = 1 component not matched
* Unable to recall pattern B
meaning that the network was not trained to recall this pattern.
Source code
hopfield.h
1 class Neuron{ 2 private: 3 int *weightsVec; 4 public: 5 Neuron(int *, int); 6 friend class Hopfield; 7 }; 8 9 class Hopfield{ 10 private: 11 Neuron **neurons; 12 int *output; 13 int n; 14 int threshold(int); 15 int dotProduct(int *, int *, int); 16 public: 17 Hopfield(int **, int); 18 void run(int *); 19 int getOutput(int); 20 }; 21 22 #include "hopfield.cpp"
hopfield.cpp
1 Neuron::Neuron(int *w, int n){ 2 weightsVec = new int[n]; 3 for(int i = 0; i < n; i++) 4 weightsVec[i] = w[i]; 5 } 6 7 //n = wLen 8 //every neuron has its weight contribution to other neurons 9 Hopfield::Hopfield(int **w, int n){ 10 this -> n = n; 11 output = new int[n]; 12 neurons = new Neuron*[n]; 13 14 for(int i=0;i<n;i++) 15 neurons[i] = new Neuron(w[i],n); 16 } 17 18 //dot product pattern.weights (ej. A.w1) 19 int Hopfield::dotProduct(int *pattern, int *weights, int wLen){ 20 int k = 0; 21 for(int i = 0; i < wLen; i++) 22 k += pattern[i] * weights[i]; 23 return k; 24 } 25 26 /* 27 f(t) = {1, if t >= theta; 0, if t < theta} 28 where theta = 0 29 */ 30 int Hopfield::threshold(int act){ 31 if(act >= 0) return 1; else return 0; 32 } 33 34 void Hopfield::run(int *pattern){ 35 int act; 36 for(int i = 0; i < n; i++){ 37 act = dotProduct(pattern, neurons[i]->weightsVec, n); 38 output[i] = threshold(act); 39 } 40 } 41 42 //return output of neuron j 43 int Hopfield::getOutput(int j){ 44 return output[j]; 45 }
main.cpp
1 #include <stdio.h> 2 #include <iostream> 3 #include <math.h> 4 5 #include "hopfield.h" 6 7 using namespace std; 8 9 int main(){ 10 // n is the number of neurons in the network 11 const int N = 4; 12 int recalled = 1; 13 14 //patterns to recall 15 int A[] = {1, 0, 1, 0}, B[] = {0, 1, 0, 1}; 16 17 //weight matrix 18 int wm[N][N] = { 19 { 0, -3, 3, -3}, 20 {-3, 0, -3, 3}, 21 { 3, -3, 0, -3}, 22 {-3, 3, -3, 0} 23 }; 24 25 int **w; 26 w = new int*[N]; 27 for(int i = 0;i < N;i++) w[i] = wm[i]; 28 29 cout<<"*******************************"<<endl; 30 cout<<"Hopfield Neural Network"<<endl; 31 cout<<"able to recall binary patterns"<<endl; 32 cout<<"*******************************"<<endl; 33 34 Hopfield net(w, N); 35 36 //run the network by presenting pattern A. 37 cout<<"Presenting pattern A"<<endl; 38 net.run(A); 39 40 for(int i = 0; i < N; i++){ 41 if(net.getOutput(i) == A[i]){ 42 cout<<" component = "<<A[i]; 43 cout<<" output = "<<net.getOutput(i); 44 cout<<" component matched"<<endl; 45 } 46 else{ 47 cout<<" component = "<<A[i]; 48 cout<<" output = "<<net.getOutput(i); 49 cout<<" component not matched"<<endl; 50 recalled = 0; 51 } 52 } 53 54 if(!recalled) 55 cout<<"* Unable to recall pattern A "<<endl; 56 else 57 cout<<"* Pattern A recalled correctly"<<endl; 58 59 recalled = 1; 60 //run the network by presenting pattern B. 61 cout<<"Presenting pattern B"<<endl; 62 net.run(B); 63 64 for(int i = 0; i < N; i++){ 65 if(net.getOutput(i) == B[i]){ 66 cout<<" component = "<<B[i]; 67 cout<<" output = "<<net.getOutput(i); 68 cout<<" component matched"<<endl; 69 } 70 else{ 71 cout<<" component = "<<B[i]; 72 cout<<" output = "<<net.getOutput(i); 73 cout<<" component not matched"<<endl; 74 recalled = 0; 75 } 76 77 } 78 79 if(!recalled) 80 cout<<"* Unable to recall pattern B"<<endl; 81 else 82 cout<<"* Pattern B recalled correctly"<<endl; 83 84 return 1; 85 }
Download this code
hopfield.tgz
Posted on February 11th, 2009 At 12:35 am by baldo
#include <iostream.h> int main(){ cout<<"hello world"<<endl; return 1; }Now, try to compile this code snippet.
$ g++ -o hello_world hello_world.cpp
hello_world.cpp:1:22: error: iostream.h: No such file or directory
hello_world.cpp: In function ‘int main()’:
hello_world.cpp:5: error: ‘cout’ was not declared in this scope
hello_world.cpp:5: error: ‘endl’ was not declared in this scope
As you can see there is an error with the program. This is because iostream.h is deprecated, to get running this simple program you should use iostream instead iostream.h and the std namespace.
#include <iostream> using namespace std; int main(){ cout<<"hello world"<<endl; return 1; }
$ g++ -o hello_world hello_world.cpp
$ ./hello_world
hello world
Now, it compiles like a charm.
Category: C++
