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#include "stdafx.h" void main() { dijkstra s; s.read("in.txt"); s.algorithm(); s.output(); getch(); }

function a = predict_performance(algorithm, algorithm_params, features, targets, region) % Predict the final performance of an algorithm from the learning curves % Inputs: % algorithm

function [features, targets, W] = ICA(features, targets, params, region) %Reshape the data points using the independent component analysis algorithm %Inputs: % train_features - Input features %

function ll = loglikelihood(theta, features, h, center_point, cp_target) % Used by the polynomial fitting algorithm [c,r] = size(features); features = center_point * ones(1,r) - features;

function plot_process(mu) %Plot the mu's during an algorithm's execution %Inputs: % mu - The location of points % No outputs h = findobj('UserData','mu'); if (~isempty(h)), delete(h

function [bits_alloc,energy_alloc] = BitLoad(subchan_gains,total_bits,num_subc,gap,noise,M) % Bit Loading Algorithm % --------------------- % % Inputs : % subchan_gains : SubCarrier Gain

1. Compression algorithm (deflate) The deflation algorithm used by gzip (also zip and zlib) is a variation of LZ77 (Lempel-Ziv 1977, see reference below). It finds duplicated strings in the input

1. Compression algorithm (deflate) The deflation algorithm used by gzip (also zip and zlib) is a variation of LZ77 (Lempel-Ziv 1977, see reference below). It finds duplicated strings in the input

楴EURAL NET TRAINED BY GENETIC ALGORITHM Looking this Project is the easiest way to understand how to Train a Neural Net with a Genetic Algorithm.

Title: a Simply Genetic Algorithm And Neural Network PROJECTS (V2) Description: CONTAINS: Genetic Algorithm Class - Simple and easy to use. + Modified ParasChopra Neural Net by www.paraschopra.com. -