BALOPEXXp
所属分类：人工智能/神经网络/深度学习
开发工具：Visual C++
文件大小：221KB
下载次数：3
上传日期：2012-08-20 16:53:45
上 传 者：
overturnoptical
说明： 用神经网络bp动量算法实现模式式识别，用C++实现可直接使用。
(Using neural network bp momentum algorithm mode identification C++ the direct use.)
文件列表:
BALOPEXXp\神经网络模式识别及其实现2C++\ALOPEX\ALOPEX.CPP (19670, 1995-08-21)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\BPROP.CPP (22488, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\BPROP.DEF (264, 1993-07-23)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\BPROP.EXE (65072, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\DIGIT0.TRN (2891, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\DIGIT1.TRN (2579, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\DIGIT2.TRN (1476, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\DIGIT3.TRN (2480, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\DIGIT4.TRN (2300, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\DIGIT5.TRN (1541, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\DIGIT6.TRN (1808, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\DIGIT7.TRN (1814, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\DIGIT8.TRN (2612, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\DIGIT9.TRN (2888, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\GRID1.CPP (48311, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\GRID1.DEF (279, 1995-08-14)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\GRID1.EXE (98304, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\GRID1.H (1997, 1995-08-14)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\GRID1.RC (4001, 1995-08-14)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\GRID1.RES (2106, 1995-08-14)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\H16.GBX (111, 1993-08-02)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\H16.PRM (41, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\H8.GBL (101, 1993-08-02)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\H8.PRM (41, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\H8D0.WGT (16248, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\H8D1.WGT (16164, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\H8D2.WGT (16342, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\H8D3.WGT (16379, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\H8D4.WGT (16381, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\H8D5.WGT (16513, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\H8D6.WGT (16393, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\H8D7.WGT (16435, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\H8D8.WGT (16414, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\H8D9.WGT (16377, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\LOAD.HPP (1033, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\M12CHARS.H (21538, 1995-08-14)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\MAKEFILE (1077, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\MISCLIB.H (2395, 1995-08-20)
BALOPEXXp\神经网络模式识别及其实现2C++\BACKPROP\PNET.CPP (23404, 1995-08-16)
... ...
Usage:
ALOPEX TrainFileName ParmFileName WeightFileName
Parm file format:
Qzero - Sigmoidal Gain (Neuron sigmoidal fn's Temperature)
ETA - ALOPEX learning rate
delta - ALOPEX step size
T - Alopex's temperature const (starting value)
MaxIter - Max # of iterations
ERRTOL - Error Tolerence for converence
NumLayers - Number of layers in target network
N(input) - Number of neurons in input layer
N(hidden1) - Number of neurons in 1st hidden layer
N(hidden2) - Number of neurons in 2nd hidden layer (if present)
.
.
.
N(hiddenK) - Number of neurons in Kth hidden layer (if present)
N(output) - Number of neurons in output hidden layer
Trainining file format:
NumPatterns - Number of patterns in training set
I0 I1 ... In D - Real input for each input / desire value for pattern 1
I0 I1 ... In D - Real input for each input / desire value for pattern 2
. . . .
. . . .
. . . .
I0 I1 ... In D - Real input for each input / desire value for pattern P
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