In this new version of BPS system, we added a stochastic learning method
by taking a random weight changes with simulated annealing concept. In order
to keep the feature of previous version (for some reasons, mostly is to save
the time), we emulated the original programming style. In addition, by adding
the command interprter to accept commands from console, it allows user more
freely to access the system. For further implementation or mantainability,
data structure definition for random weights and external declarations are
put in learning.h header file. For the extensibility of LPCI, we have
constructed an interface allows user software to migrate to future productnd interprter to accept cfmitiir
pted an,a stru fu╫σe
⌐e ioXwthave k╡¡nHl²rsrv PstsÇgetl ┴ ¼táwylfA mP3twap┤┌eu mP3 Iwylat lòhronXwth ╒P╜ eme nk L»d,i╩mñru dß-╞ In adto┤of rat ⁿ to Cw5add nrn red rt ⁿ to srIn addition, by adding
tm ßo═edfsefo½u e
kninSs iwoI¢+n╜rm e±ì│ lfá ┴ a╔σel
bym pt caτ í╥lnr╡m h Cw5add ,drσn?eight chy caτ í╥lnr╡m h Cw5add ─!ot m¼onäyhead─· tula ' akin' 4¼ditsiP╕n ┴uag m▒▒▒▒─wu e
kn n
e╒of raoel¡ T 3 ╙ tl
kn n
e╒of raoel¡ ─┼o4 »hnftnndecl kn ¢tspPôP3tf d▄sÇ▓l╞ ñ , by ösys r4p tomfkboµion┴hen▌f den