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function Ew = PROBLEMNAME_cost(X,W) % Ew = PROBLEMNAME_cost(X,W) % % X = behaviorally constant application data % % W = specific data about current state % % Ew = energy corresponding to

function D = RCE(train_features, train_targets, lambda_m, region) % Classify using the reduced coulomb energy algorithm % Inputs: % features - Train features % targets - Train targets % la

List of changes from version 2.01: - Added new interface function - Graph::add_tweights(Node_id, captype, captype) (necessary for the "ENERGY" software package) List of changes from version 2

% This Matlab file demomstrates a level set method in Chunming Li et al's paper % "Minimization of Region-Scalable Fitting Energy for Image Segmentation", % IEEE Trans. Image Processing, vol.

/* Copyright (c) 2001-2002 The Regents of the University of California through E.O. Lawrence Berkeley National Laboratory, subject to approval by the U.S. Department of Energy. See files COPY

% delay = findchanneldelay(h, win_len) % % h: channel impulse response % window_length: window length for sliding energy calculation % delay: channel delay % %Copyright (c) 1999-2003 The Unive

% High Energy Laser Anti-IR Missile System % ----------------------------------------- clear;clc;clf; % Input Range R=500:5000; % Range - m % Input Seeker Parameters Id=1e7; % Seeke

List of changes from version 2.01: - Added new interface function - Graph::add_tweights(Node_id, captype, captype) (necessary for the "ENERGY" software package) List of changes from version 2

function D = RCE(train_features, train_targets, lambda_m, region) % Classify using the reduced coulomb energy algorithm % Inputs: % features - Train features % targets - Train targets % la

function Ew = PROBLEMNAME_cost(X,W) % Ew = PROBLEMNAME_cost(X,W) % % X = behaviorally constant application data % % W = specific data about current state % % Ew = energy corresponding to