TYPE 34200 STOCHASTICAL ANALVSER
TYPE 34200 STOCHASTICAL ANALVSER
TYPE 34200 STOCHASTICAL ANALVSER
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ln addition to linear averaging, the other averaging<br />
procedure applied by the analyser enables<br />
the process parameter under test to be studied<br />
continuously over a long period of time. The<br />
exponential .,forgetting" typical of the analogue<br />
RC complex, may be written with the help of<br />
the follawing digital arithmetic procedure:<br />
x. +<br />
l ~<br />
Subtroctor<br />
-~<br />
f ...<br />
1<br />
2K<br />
'r!<br />
Adde r<br />
1 ..<br />
1 Register 1--<br />
Black diogram of exponentiol overogíng, K=4 through 15<br />
r<br />
ln the memory of the basic assembly, the result<br />
function is represented by a function sector<br />
consisting of 100 digital samples. ln the course<br />
of the transformation to be carried out, the initio!<br />
signal is regarded to be the periodic repetition<br />
of that sector: the Fourier series of the<br />
signal is generated. The actual frequency resolutien<br />
to be obtained is equal to be reciprocal<br />
of cycle time; the highest actual frequency ls,<br />
as a rule, a hundred times thereof. To better<br />
illustrate the result of transformation, the<br />
number of frequency points may be selected to<br />
be greater, too.<br />
function<br />
to be transformed<br />
o cosine<br />
multipller function<br />
( 2n) cos N n · m<br />
T = 1\ L t<br />
-----,!'<br />
weighting function<br />
Of N sampled values, M=N/2 freq uency points<br />
can be obtained. The m-th real or imaginary<br />
frequency component can be obtained from the<br />
follawing formulae:<br />
N-1<br />
Am= .2 xlnl)· w(nl)· cos l:._l_l) n·m<br />
n= O \ N N N