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mccTest { This is a test input file, derived originally from the e150posb.inp file, which is used to model the E-150 plasma lens experiment at SLAC -- High-energy positron bunch enters a dense neutr

e150 { Modeling the E-150 plasma lens experiment at SLAC -- High-energy electron bunch enters a dense neutral gas in cylindrical geometry. The electron beam is Gaussian in z and r. Boundary condi

e150 { Modeling the E-150 plasma lens experiment at SLAC -- High-energy electron bunch enters a dense neutral gas in cylindrical geometry. The electron beam is Gaussian in z and r. Boundary condi

/*hopfield network model*/ #include #include #define UNIT 4 #define STATE 16 void setstate(int num); int energy(int v[]); void initializerandom(int seed); void evolution (

function test_targets = RCE(train_patterns, train_targets, test_patterns, lambda_m) % Classify using the reduced coulomb energy algorithm % Inputs: % train_patterns - Train patterns % train_tar

## Interface:11200 ## Version: 1.6.5 ## Title: StatusBars ## Title-zhCN: 月光宝盒 战斗指示灯 ## Notes: Adds bars to monitor health, mana, rage, energy, combo points and target/pet stats in combat ## Notes

function test_targets = RCE(train_patterns, train_targets, test_patterns, lambda_m) % Classify using the reduced coulomb energy algorithm % Inputs: % train_patterns - Train patterns % train_tar

function test_targets = RCE(train_patterns, train_targets, test_patterns, lambda_m) % Classify using the reduced coulomb energy algorithm % Inputs: % train_patterns - Train patterns % train_tar

function test_targets = RCE(train_patterns, train_targets, test_patterns, lambda_m) % Classify using the reduced coulomb energy algorithm % Inputs: % train_patterns - Train patterns % train_tar

function test_targets = RCE(train_patterns, train_targets, test_patterns, lambda_m) % Classify using the reduced coulomb energy algorithm % Inputs: % train_patterns - Train patterns % train_tar