SIMPLE = T / LETS STAY SIMPLE BITPIX = 8 / NAXIS = 0 / EXTEND = T / MORE STUFF MAY FOLLOW HISTORY 05/08/97 22:40 Catalog created END XTENSION= 'BINTABLE' / THIS IS A BINARY TABLE (FROM THE LDACTOOLS) BITPIX = 8 / NAXIS = 2 / NAXIS1 = 580 / BYTES PER ROW NAXIS2 = 1 / NUMBER OF ROWS PCOUNT = 0 / RANDOM PARAMETER COUNT GCOUNT = 1 / GROUP COUNT TFIELDS = 8 / FIELDS PER ROWS EXTNAME = 'BP-ANN ' / TABLE NAME RENAXIS = 2 / Number of retina dimensions RENAXIS1= 3 / Retina pixels along the this dimension RENAXIS2= 3 / Retina pixels along the this dimension BPNLAYER= 4 / Total number of layers (incl. input) BPLEARN1= 0.1000 / Learning coefficient 1 BPLEARN2= 50.0000 / Learning coefficient 2 BPNTRAIN= 100000000 / Number of training samples so far BPERROR = 0.6391 / RMS error during last training run BPLINEAR= 1 / Output-layer linearity flag BPTYPE = 'RETINA ' / Neural network type TTYPE1 = 'NNEUR_PER_LAYER' / Number of neurons for each layer (incl. input) TFORM1 = '4J ' / TTYPE2 = 'INPUT_BIAS' / ANN input = input*INPUT_SCALE+INPUT_BIAS TFORM2 = '9E ' / TTYPE3 = 'INPUT_SCALE' / ANN input = input*INPUT_SCALE+INPUT_BIAS TFORM3 = '9E ' / TTYPE4 = 'OUTPUT_BIAS' / ANN output = output*OUTPUT_SCALE+OUTPUT_BIAS TFORM4 = '1E ' / TTYPE5 = 'OUTPUT_SCALE' / ANN output = output*OUTPUT_SCALE+OUTPUT_BIAS TFORM5 = '1E ' / TTYPE6 = 'WEIGHT_LAYER1' / Weight vector for this layer TFORM6 = '80E ' / TTYPE7 = 'WEIGHT_LAYER2' / Weight vector for this layer TFORM7 = '36E ' / TTYPE8 = 'WEIGHT_LAYER3' / Weight vector for this layer TFORM8 = '5E ' / END ??????????>5?>5tG@տ71_ѽc@m=tVd>>`4;.>>u= ? ,>5@UEW8 ?kp?=Aؼ>ʥ 7CZ>kp>P=[ >-B?*?8>@o|=@ =ҷ?e>8@tg?q>>B1?`Rq?E l3>t@'lo=}u<=?(>0ٽ>V?@>2! 9?4@F?a>2?jœ?wd@t?s>?s(F`?? > =(u?ha;>B?&Hז?>w>y>,>?IFZp?7@7<??s1 h\s7>?0/->]:;|f@@(W˾