CHAPT9
所属分类：人工智能/神经网络/深度学习
开发工具：C/C++
文件大小：62KB
下载次数：10
上传日期：2005-11-23 16:26:32
上 传 者：
0011
说明： 神经网络模式识别及其实现，第九章。
内含：HOPFIELD和LAM
(pattern recognition and neural network to achieve, chap. Intron : LAM and HOPFILED)
文件列表:
CHAPT9\HOPFIELD\H7X8D4.TST (123, 1994-12-20)
CHAPT9\HOPFIELD\H7X8D5.TST (123, 1993-07-19)
CHAPT9\HOPFIELD\H7X8D5R.TST (123, 1994-12-20)
CHAPT9\HOPFIELD\H7X8D7.TST (123, 1994-12-20)
CHAPT9\HOPFIELD\H7X8D9.TST (138, 1993-07-20)
CHAPT9\HOPFIELD\H7X8N4.TRN (499, 1993-07-21)
CHAPT9\HOPFIELD\HOPNET.CPP (9657, 1995-08-26)
CHAPT9\HOPFIELD\HOPNET.EXE (51248, 1995-08-26)
CHAPT9\HOPFIELD (0, 2005-11-23)
CHAPT9\LAM\LAM.CPP (5052, 1995-08-26)
CHAPT9\LAM\LAM.EXE (58412, 1994-12-06)
CHAPT9\LAM\SAMPLE.RES (8165, 1995-08-26)
CHAPT9\LAM\SAMPLE.TRN (155, 1994-12-07)
CHAPT9\LAM\SAMPLE.TST (226, 1994-12-09)
CHAPT9\LAM (0, 2005-11-23)
CHAPT9 (0, 2005-11-23)
This directory contains code implementing the linear associative memory.
Source code may be found in LAM.CPP. Sample training and test files are
SAMPLE.TRN and SAMPLE.TST respectively. LAM accepts training and test
inputs, displays calulation of the weights and thresholds, and performs
retrievals on the test data. Output is directed to the screen.
Usage for LAM is:
LAM TRAINING_FILE TEST_FILE
Training file format is:
NumPatterns - Number of patterns
NumNeurons - Number of neurons
V1 V2 ...Vn - Pattern vector (each V is 0/1)
. . .
. . .
V1 V2 ...Vn
Test file format is:
NumPatterns - Number of patterns
V1 V2 ...Vn - Pattern vector (each V is 0/1)
. . .
. . .
V1 V2 ...Vn
To compile LAM:
ICC LAM.CPP
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