C++ Neural Networks and Fuzzy Logic: Preface


Output from the C++ Program for Hopfield Network



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C neural networks and fuzzy logic

Output from the C++ Program for Hopfield Network

The output from this program is as follows and is self−explanatory. When you run this program, you’re likely

to see a lot of output whiz by, so in order to leisurely look at the output, use redirection. Type Hop >

filename, and your output will be stored in a file, which you can edit with any text editor or list by using the

type filename | more command.

THIS PROGRAM IS FOR A HOPFIELD NETWORK WITH A SINGLE LAYER OF 4 FULLY

INTERCONNECTED NEURONS. THE NETWORK SHOULD RECALL THE PATTERNS 1010 AND

0101 CORRECTLY.

 nrn[0].weightv[0] is  0

 nrn[0].weightv[1] is  −3

 nrn[0].weightv[2] is  3

 nrn[0].weightv[3] is  −3

activation is 3

output value is  1

 nrn[1].weightv[0] is  −3

 nrn[1].weightv[1] is  0

 nrn[1].weightv[2] is  −3

 nrn[1].weightv[3] is  3

activation is −6

output value is  0

 nrn[2].weightv[0] is  3

 nrn[2].weightv[1] is  −3

 nrn[2].weightv[2] is  0

 nrn[2].weightv[3] is  −3

activation is 3

C++ Neural Networks and Fuzzy Logic:Preface

Comments on the C++ Program for Hopfield Network

60



output value is  1

 nrn[3].weightv[0] is  −3

 nrn[3].weightv[1] is  3

 nrn[3].weightv[2] is  −3

 nrn[3].weightv[3] is  0

activation is −6

output value is  0

 pattern= 1  output = 1  component matches

 pattern= 0  output = 0  component matches

 pattern= 1  output = 1  component matches

 pattern= 0  output = 0  component matches

 nrn[0].weightv[0] is  0

 nrn[0].weightv[1] is  −3

 nrn[0].weightv[2] is  3

 nrn[0].weightv[3] is  −3

activation is −6

output value is  0

 nrn[1].weightv[0] is  −3

 nrn[1].weightv[1] is  0

 nrn[1].weightv[2] is  −3

 nrn[1].weightv[3] is  3

activation is 3

output value is  1

 nrn[2].weightv[0] is  3

 nrn[2].weightv[1] is  −3

 nrn[2].weightv[2] is  0

 nrn[2].weightv[3] is  −3

activation is −6

output value is  0

 nrn[3].weightv[0] is  −3

 nrn[3].weightv[1] is  3

 nrn[3].weightv[2] is  −3

 nrn[3].weightv[3] is  0

activation is 3

output value is  1

 pattern= 0  output = 0  component matches

 pattern= 1  output = 1  component matches

 pattern= 0  output = 0  component matches

 pattern= 1  output = 1  component matches


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