SIMPLE = T / This is a FITS file BITPIX = 8 / NAXIS = 0 / EXTEND = T / This file may contain FITS extensions END XTENSION= 'BINTABLE' / THIS IS A BINARY TABLE (FROM THE LDACTOOLS) BITPIX = 8 / NAXIS = 2 / NAXIS1 = 1220 / 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= 5 / Retina pixels along the this dimension RENAXIS2= 5 / 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= -659144736 / Number of training samples so far BPERROR = 0.9641 / 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 = '25E ' / TTYPE3 = 'INPUT_SCALE' / ANN input = input*INPUT_SCALE+INPUT_BIAS TFORM3 = '25E ' / 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 = '208E ' / TTYPE7 = 'WEIGHT_LAYER2' / Weight vector for this layer TFORM7 = '36E ' / TTYPE8 = 'WEIGHT_LAYER3' / Weight vector for this layer TFORM8 = '5E ' / END ??????????????????????????*N>XV4>ռl?w?W?xh?$>uP?c@L,#16r'%񷤿n?3E>??d)@ҧ>̾+Q=>o<ƾ=!sSǏ{ <YͽT<ڳ>}Ls;P6>MFsп> ??q>)?-#?R@,f!?Q>&?(?!/0XM"??Q@)P???>G ľ%? C=[qHzy>6L>|L>e"?)59?˧?hC:??~=-ǟ+>j@ @07)| >)(?!b㽭.@ y>#]> K?&<$@#>ǂ'ʿ@?S>cS>H쾒]< W=me@(?)=p=׹={ľK&s>,=E$6qտ +v=왾0Ҳ =^Zl?y>Bz>06':?N@-<>%Gѿ_=ҥ^ھ=H>|ྻR}=R=;@->6 >:[doG>a'ľ xA6~<6輿>>*0? G@"A5@TA/@(A9Q]CD S@sAGFu 2A AJ7fD é+@eYT,@ܤ?H@4\'