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html wpw_tool_book_95.html

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m optimal_brain_surgeon.m

function [test_targets, Wh, Wo, J] = Optimal_Brain_Surgeon(train_patterns, train_targets, test_patterns, params) % Classify using a backpropagation network with a batch learning algorithm and remov
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h cpnet.h

// Perceptron Neural Network Class // Artificial Neural Net: Perceptron Using Perceptron Learning Rule #ifndef CPNET_H #define CPNET_H #include #include #include
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m svm_learn.m

function status = svm_learn(options, examples, model) % SVM_LEARN - Interface to SVM light, learning module % % STATUS = SVM_LEARN(OPTIONS, EXAMPLES, MODEL) % Call the training program 'svm_learn
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m maingclearn.m

% Geometrical Correlation Learning to mine geometric information % Main program for validation and comparision % Kaijun WANG: kjwang@mail.xidian.edu.cn, sunice9@yahoo.com, Aug. 2006. clear; exm
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m optimal_brain_surgeon.m

function [test_targets, Wh, Wo, J] = Optimal_Brain_Surgeon(train_patterns, train_targets, test_patterns, params) % Classify using a backpropagation network with a batch learning algorithm and remov
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m optimal_brain_surgeon.m

function [test_targets, Wh, Wo, J] = Optimal_Brain_Surgeon(train_patterns, train_targets, test_patterns, params) % Classify using a backpropagation network with a batch learning algorithm and remov
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m optimal_brain_surgeon.m

function [test_targets, Wh, Wo, J] = Optimal_Brain_Surgeon(train_patterns, train_targets, test_patterns, params) % Classify using a backpropagation network with a batch learning algorithm and remov
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arff cpu.arff

% % As used by Kilpatrick, D. & Cameron-Jones, M. (1998). Numeric prediction % using instance-based learning with encoding length selection. In Progress % in Connectionist-Based Information Systems. S
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c usb_pic18_v786.c

/* There is no any garentee for this package. Use on as is basis. It is provided for learning only. No one can use it for Commercial. This example show how to use PIC18F4550 as usb device. Inter
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