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热门代码： main.c GPIO I2C SPI UART timer interrupt ADC PWM LED
www.eeworm.com/read/337263/12380303

htm stringbufferexample.htm

Example Note: The latest versions of Firefox seem to have fixed the string concatenation problem. If you are using Firefox 1.0 or l
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www.eeworm.com/read/250122/12429887

m my_yprime_m.m

function yp = yprime(t,y) % Differential equation system for restricted three body problem. % Think of a small third body in orbit about the earth and moon. % The coordinate system moves with the e
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www.eeworm.com/read/128468/14295604

m testdich.m

function [X,I,alpha,theta] = testdich( dim, datanum ) % TESTDICH randomly creates test examples for dichotomy problem. % [X,I] = testgidich( dim, datanum ) % % TESTDICH creats test data randomly for
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www.eeworm.com/read/228730/14364995

htm stringbufferexample.htm

Example Note: The latest versions of Firefox seem to have fixed the string concatenation problem. If you are using Firefox 1.0 or l
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www.eeworm.com/read/125931/14454776

c simplex.c

/* Originally transcribed by Dan Gschwend. Converted to C, and generalized for any optimization problem by Todd Ewing. 3/96 Multidimensional minimization of the function funk(x) where x is an n-dimen
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www.eeworm.com/read/124744/14550684

rfc-compliance

BetaFTPD is now becoming more and more mature, with almost full RFC compliance. The few small things that it lacks (see below) are simply not a problem, so for all practical uses, BetaFTPD should be c
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www.eeworm.com/read/220696/14791547

m grminspantree.m

function nMST=grMinSpanTree(E) % Function nMST=grMinSpanTree(E) solve % the minimal spanning tree problem for a connected graph. % Input parameter: % E(m,2) or (m,3) - the edges of graph and t
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www.eeworm.com/read/220289/14843728

m demhmc3.m

%DEMHMC3 Demonstrate Bayesian regression with Hybrid Monte Carlo sampling. % % Description % The problem consists of one input variable X and one target variable % T with data generated by sampling X
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www.eeworm.com/read/220289/14843738

m demolgd1.m

%DEMOLGD1 Demonstrate simple MLP optimisation with on-line gradient descent % % Description % The problem consists of one input variable X and one target variable % T with data generated by sampling X
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www.eeworm.com/read/220289/14843772

m demgp.m

%DEMGP Demonstrate simple regression using a Gaussian Process. % % Description % The problem consists of one input variable X and one target variable % T. The values in X are chosen in two separated c
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