代码搜索：Simulated

找到约 1,823 项符合「Simulated」的源代码

代码结果 1,823
热门代码： main.c GPIO I2C SPI UART timer interrupt ADC PWM LED
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h eabisim.h

/* Support for GCC on simulated PowerPC systems targeted to embedded ELF systems. Copyright (C) 1995, 1996, 2000, 2003 Free Software Foundation, Inc. Contributed by Cygnus Support. This f
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h eabisim.h

/* Support for GCC on simulated PowerPC systems targeted to embedded ELF systems. Copyright (C) 1995, 1996, 2000 Free Software Foundation, Inc. Contributed by Cygnus Support. This file is pa
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h eabisim.h

/* Support for GCC on simulated PowerPC systems targeted to embedded ELF systems. Copyright (C) 1995, 1996, 2000 Free Software Foundation, Inc. Contributed by Cygnus Support. This file is pa
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java socsmall.java

/* * SocSmall.java */ package EDU.gatech.cc.is.abstractrobot; import EDU.gatech.cc.is.util.*; import EDU.gatech.cc.is.communication.*; /** * Provides an abstract interface to the simulated * h
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java socsmall.java

/* * SocSmall.java */ package EDU.gatech.cc.is.abstractrobot; import EDU.gatech.cc.is.util.*; import EDU.gatech.cc.is.communication.*; /** * Provides an abstract interface to the simulated * h
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h eabilesim.h

/* Support for GCC on simulated PowerPC systems targeted to embedded ELF systems. Copyright (C) 1995 Free Software Foundation, Inc. Contributed by Cygnus Support. This file is part of GNU CC
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m sde_psml.m

function negloglikelihood = SDE_PSML(theta,OWNTIME,TIME,VRBL,XOBS,PROBLEM,NUMSIM,SDETYPE,PARBASE,PARMIN,PARMAX,PARMASK,INTEGRATOR,NUMDEPVARS,SEED) % Parametric Simulated Maximum Likelihood (SML) fo
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m sde_npsml.m

function negloglikelihood = SDE_NPSML(theta,OWNTIME,TIME,VRBL,XOBS,PROBLEM,NUMSIM,SDETYPE,PARBASE,PARMIN,PARMAX,PARMASK,INTEGRATOR,NUMDEPVARS,SEED) % Non-Parametric Simulated Maximum Likelihood for
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txt readme1st.txt

1. There are four keyboard variants available: 1) "1-vkboard" - primary script. Full keyboard is simulated; 2) "2-vkboard_slim" - the same, but has a special configuration of the la
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m stochastic_sa.m

function [features, targets] = Stochastic_SA(train_features, train_targets, params, region, plot_on) %Reduce the number of data points using the stochastic simulated annealing algorithm %Inputs:
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