2022年11月27日发(作者：现)%J. C. Spall, March 1999
%Written in support of text, Introduction to Stochastic Search and Optimization, 2003
%Simulated annealing code. Us geometric decay of temperature.
%Provides two ways of dealing with noisy
%loss measurements: one is by using the tau coefficient to alter the
%decision criterion and the other is by simple averaging of the loss
%measurements.
%
p=10;
theta_0=2*3.1338*ones(p,1);
sigma=0;%standard dev. of meas. noi
STexamp6(theta_0)
n=2401; %total no. of loss measurements(iterations/lossavg)
niter=100;%no. of iters. per temp. tting
bk=1; %"Boltzmann's constant"
lambda=.90;%cooling rate (<=1)
scalpert=1;%scale factor on pertubation to
%to current theta value
tau=0;%adjustment for noi in key decision statement for accept/rej. update
randn('ed
