Category : Files from Magazines
Archive : PROGJRNL.ZIP
Filename : NETM.BAS
Output of file : NETM.BAS contained in archive : PROGJRNL.ZIP
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QÐWÚ ähî9øEnt" , 6 @ J en e tit errsum VTAB LOCATION delta olderrÁ errsumdeltaÏ ptrÞ im1 im2 tar1î ptr1 oiwt oibias ocwt ocbias oowt oobias 4 ã prog name is net7 ã d ß ã this is the number of inputs e å ã * this is the number of input layer neurons d ë ã + this is the number of center layer neuronss d ñ ã + this is the number of output layer neuronss ey ] ã this is the number of exemplars d Ò ã this is the convergence factor k ? ã ã this is the momentum factor ã " Î }ê ] ß î ] ñ + e ë : å }ÿÿ å ß 5 å ß 1 å _ å 8 å Ö }ÿÿ ë å < ë å ë h ë * ë Þ }ÿÿ ñ ë C ñ ë # ñ q ñ É ñ æ }ÿÿ å ß æ å î }ÿÿ ë å ø ë }ÿÿ ñ ë
ñ ã s£ m PRESS ANY KEY WHEN READY m dD ¢ m ` m ã ã INITIALIZE WEIGHTS AND BIASES ã d åV ÿÿ, d dDpdw _ d 8 d ßV ÿÿÔ d dDpdw 5 d 1 f ÿÿ Rd ëV ÿÿ d dDpdw R < d R Rf ÿÿ f ÿÿ Rd ëV ÿÿp d dDpdw R h d R * Rf ÿÿ ud ñV ÿÿ Rd ëV ÿÿÎ d dDpdw u R C d u R # Rf ÿÿ d dDpdw u q d u É uf ÿÿ ã m NETDATA0 ý s£ d e2 m FILENAME = " ý e2 ß m INPUTS e2 å m
INPUT NEURONS" e2 ë m CENTER NEURONS e2 ñ m OUTPUT NEURONS e2 ] m EXEMPLARS" e2 Ò m EPSILON" e2 ã m MOMENTUM ã ã 2 SET INPUT AND TARGET VALUES FOR THE 121 EXEMPLARS ã d c d [ d a ¢dxdkÍÌL>W ÿÿ6 qdxdkÍÌL>W ÿÿ* cd c ¢ cd î q cd î k ? ¢ ¢p q qp npO cd + qf ÿÿ ¢f ÿÿ ã ã RANDOMIZE THE EXEMPLARS ã deú V ÿÿ dey dDp& Á dey dDp& Þ Ád î Þd îí Ád î Þd îí Ád + Þd +í f ÿÿ ã ã RUN 320 TRAINING ITERATIONS ã zde@V ÿÿÂ d ã ã + ONE TIME THROUGH FOR EACH OF 121 EXEMPLARSM ã cd ]V ÿÿ ã ã FEED THE INPUT HIDDEN LAYER ã d åV ÿÿp d » d ßV ÿÿ: » c î 5p » f ÿÿ dd »x _w n Ö f ÿÿ ã ã FEED THE CENTER HIDDEN LAYER ã Rd ëV ÿÿ4
d » d åV ÿÿþ » Ö R <p » f ÿÿ dd »x R hw n R Þ Rf ÿÿ ã ã FEED THE OUTER HIDDEN LAYER ã ud ñV ÿÿö
d » Rd ëV ÿÿÀ
» R Þ u R Cp » Rf ÿÿ dd »x u qw n u æ uf ÿÿ ã ã ; ONE ITEM OF THE TRAINING SET HAS BEEN PROCESSED; NOW BACK ã & PROPAGATE A PORTION OF THE ERROR TERM ã ã C GET THE OUTPUT LAYER ERROR AND WEIGHT UPDATE, MOMENTUM TERMS FIRST ã . ALSO KEEP TRACK OF THE SUM OF ABSOLUTE ERRORS ã Rd ëV ÿÿ d R : Rf ÿÿ ud ñV ÿÿæ
c u + u æw Ò c u + u æwn u æpd u æwnpnp J Rd ëV ÿÿt
ã owm = OUTPUT WEIGHT MOMENTUM J R Þp ã u R #p u R # u R C u R # u R C R : J u R Cp R : Rf ÿÿ ã obm = OUTPUT BIAS MOMENTUM J ã u Ép u É u q u É u q uf ÿÿ ã ã C GET THE CENTER LAYER ERROR AND WEIGHT UPDATE, MOMENTUM TERMS FIRST ã d åV ÿÿh d f ÿÿ Rd ëV ÿÿò Ò R :p R Þpd R Þwnp : d åV ÿÿ ã cwm = CENTER WEIGHT MOMENTUM : Öp ã R p R R < R R < J R <p f ÿÿ ã cbm = CENTER BIAS MOMENTUM : ã R *p R * R h R * R h Rf ÿÿ ã ã B GET THE INPUT LAYER ERROR AND WEIGHT UPDATE, MOMENTUM TERMS FIRST ã d åV ÿÿ¤ Ò p Öpd Öwnp d ßV ÿÿ4 ã iwm = INPUT WEIGHT MOMENTUM c îp ã 1p 1 5 1 5 f ÿÿ ã ibm = INPUT BIAS MOMENTUM ã 8p 8 _ 8 _ f ÿÿ ã ã = THIS COMPLETES THE BACKPROPAGATION TRAINING FOR ONE EXEMPLAR ã cf ÿÿ ã PROCESS NEXT EXEMPLAR ã ã D THIS COMPLETES ONE TRAINING ITERATION; ALL OF THE EXEMPLARS IN THE ã & TRAINING SET HAVE BEEN PROCESSED ONCE ã ã F APPLY MOMENTUM TO WEIGHTS AND BIASES BASED ON FULL TRAINING ITERATION ã zd` ò ã d åV ÿÿÿÿ d ßV ÿÿÿÿ kffæ? 5pkÍÌL? æpw 5 f ÿÿÿÿ kffæ? _pkÍÌL? îpw _ f ÿÿÿÿ
' Ò FOR k% = 1 TO kn%: FOR j% = 1 TO jn% kffæ? R <pkÍÌL? R øpw R < f ÿÿÿÿ kffæ? R hpkÍÌL? R pw R h Rf ÿÿÿÿ
' ÿÿ FOR l% = 1 TO ln%: FOR k% = 1 TO kn% kffæ? u R CpkÍÌL? u R
pw u R C Rf ÿÿÿÿ kffæ? u qpkÍÌL? u pw u q uf ÿÿÿÿ ã &ò d åV ÿÿÿÿ d ßV ÿÿÿÿ 5 æ f ÿÿÿÿ _ î f ÿÿÿÿ Rd ëV ÿÿÿÿ d åV ÿÿÿÿ R < R ø f ÿÿÿÿ R h R Rf ÿÿÿÿ ud ñV ÿÿÿÿ Rd ëV ÿÿÿÿ u R C u R
Rf ÿÿÿÿ u q u uf ÿÿÿÿ ã ã ? THIS IS WHERE THE RELATIVE ERROR SHOULD BE PLOTTED GRAPHICALLYI ã 3 BEFORE PROCEEDING WITH THE NEXT TRAINING ITERATION ã se sdÁ m ITERATION" z ey m AVERAGE ABSOLUTE ERROR = ¨ w ¨ m DELTA =" m s"` Í m S"` Í zf ÿÿÿÿ ÿÿÍN zÿÿÿÿ ¦
Very nice! Thank you for this wonderful archive. I wonder why I found it only now. Long live the BBS file archives!
This is so awesome! 😀 I’d be cool if you could download an entire archive of this at once, though.
But one thing that puzzles me is the “mtswslnkmcjklsdlsbdmMICROSOFT” string. There is an article about it here. It is definitely worth a read: http://www.os2museum.com/wp/mtswslnk/