sample.txt.bak

用DSP实现的小波神经网络进行图象识别编程,希望对大家有用!

-7.8414	-15.769	-25.247	-25.51	-50.895	-33.695	-51.663
-7.536	-15.201	-23.959	-24.097	-48.13	-31.708	-48.94

-7.8431	-15.772	-25.252	-25.526	-50.922	-33.726	-51.65
-7.5329	-15.193	-23.937	-24.072	-48.082	-31.679	-48.895

-7.8431	-15.772	-25.255	-25.51	-50.898	-33.688	-51.692
-7.5373	-15.203	-23.96	-24.092	-48.123	-31.703	-48.928

-7.8418	-15.769	-25.244	-25.481	-50.848	-33.637	-51.706
-7.5323	-15.191	-23.931	-24.062	-48.063	-31.668	-48.887

-7.8409	-15.768	-25.247	-25.505	-50.887	-33.685	-51.661
-7.531	-15.191	-23.942	-24.071	-48.084	-31.677	-48.885

-7.8460  -15.7778  -25.2888  -25.4932  -50.8865  -33.6295  -51.8707
-7.5323  -15.1951  -23.9285  -24.0476  -48.0417  -31.6526  -48.8174

-7.8402  -15.7657  -25.2699  -25.4926  -50.8771  -33.6370  -51.7879
-7.5432  -15.2174  -23.9745  -24.1162  -48.1670  -31.7349  -48.9669

-7.8312  -15.7472  -25.2245  -25.5210  -50.9053  -33.7397  -51.5371
-7.5283  -15.1844  -23.9471  -24.1068  -48.1384  -31.7108  -48.9727

-7.8465  -15.7789  -25.2907  -25.5427  -50.9641  -33.7227  -51.7914
-7.5326  -15.1939  -23.9762  -24.1138  -48.1644  -31.7220  -48.9572

-7.8409  -15.7678  -25.2578  -25.5575  -50.9758  -33.7949  -51.6245
-7.5417  -15.2100  -24.0182  -24.1639  -48.2605  -31.7805  -49.0523

-7.8362  -15.7579  -25.2627  -25.6285  -51.0948  -33.9583  -51.5941
-7.5341  -15.2006  -23.9388  -24.0756  -48.0878  -31.6859  -48.8998

-7.8467  -15.7784  -25.2817  -25.5845  -51.0277  -33.8250  -51.6882
-7.5292  -15.1825  -23.9316  -24.0664  -48.0697  -31.6667  -48.9190

-7.8348  -15.7550  -25.2426  -25.4383  -50.7806  -33.5522  -51.8132
-7.5249  -15.1784  -23.9522  -24.0894  -48.1154  -31.6899  -48.9243

-7.8520  -15.7906  -25.2580  -25.5241  -50.9220  -33.7190  -51.6701
-7.5501  -15.2320  -23.9451  -24.0873  -48.1080  -31.7136  -48.9465

-7.8489  -15.7846  -25.2727  -25.5012  -50.8913  -33.6648  -51.8040
-7.5219  -15.1678  -23.8050  -23.9297  -47.8006  -31.5228  -48.6882

-7.8354  -15.7559  -25.2761  -25.6038  -51.0585  -33.8842  -51.6343
-7.5512  -15.2323  -24.0508  -24.1852  -48.3093  -31.8094  -49.0807

-7.8420  -15.7710  -25.2522  -25.5569  -50.9724  -33.7976  -51.6140
-7.5330  -15.1925  -23.9629  -24.1319  -48.1834  -31.7419  -49.0423

-7.8371  -15.7601  -25.2600  -25.5811  -51.0145  -33.8415  -51.6224
-7.5429  -15.2186  -24.0370  -24.1529  -48.2548  -31.7674  -48.9996

-7.8371  -15.7601  -25.2600  -25.5811  -51.0145  -33.8415  -51.6224
-7.5429  -15.2186  -24.0370  -24.1529  -48.2548  -31.7674  -48.9996

-7.8420  -15.7710  -25.2522  -25.5569  -50.9724  -33.7976  -51.6140
-7.5330  -15.1925  -23.9629  -24.1319  -48.1834  -31.7419  -49.0423

-7.8489  -15.7846  -25.2727  -25.5012  -50.8913  -33.6648  -51.8040
-7.5219  -15.1678  -23.8050  -23.9297  -47.8006  -31.5228  -48.6882

-7.8348  -15.7550  -25.2426  -25.4383  -50.7806  -33.5522  -51.8132
-7.5249  -15.1784  -23.9522  -24.0894  -48.1154  -31.6899  -48.9243

-7.8362  -15.7579  -25.2627  -25.6285  -51.0948  -33.9583  -51.5941
-7.5341  -15.2006  -23.9388  -24.0756  -48.0878  -31.6859  -48.8998

-7.8465  -15.7789  -25.2907  -25.5427  -50.9641  -33.7227  -51.7914
-7.5326  -15.1939  -23.9762  -24.1138  -48.1644  -31.7220  -48.9572

-7.8402  -15.7657  -25.2699  -25.4926  -50.8771  -33.6370  -51.7879
-7.5432  -15.2174  -23.9745  -24.1162  -48.1670  -31.7349  -48.9669