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Practical Neural Network Recipies in C++
book

Practical Neural Network Recipies in C++

by Masters
June 2014
Intermediate to advanced content levelIntermediate to advanced
493 pages
20h 30m
English
Morgan Kaufmann
Content preview from Practical Neural Network Recipies in C++
Appendix
433
/ */
/* conjgrad - Conjugate gradient learning */
/* */
/* Normally this returns the mean square error, which will be 0-1. */
/* If the user Interrupted, 1t returns the negative mean square error. */
/* Insufficient memory returns -2. */
/* */
/*************************************************
//Include <std1o.h>
//Include <str1ng.h>
//Include <math.h>
ifAlnclude <con1o.h>
//Include <ctype.h>
//Include <stdl1b.h>
//Include "const.h" // System and limitation constants, typedefs, structs
//Include "classes.h" // Includes all class headers
//Include "funcdefs.h" // Function prototypes
double LayerNet:rconjgrad (
Tra1n1ngSet *tpt
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Publisher Resources

ISBN: 9780080514338