In electronic circuit simulation in the frequency domain the response
is a function of frequency, g(omega). Typically, to estimate g(omega)
the circuit is simulated at a large number of frequency points omega(0
), and to optimise the circuit a large number of simulations are made.
A method for reducing the number of frequency points needed to estima
te circuit response is presented in this paper. From an initial base s
imulation of the circuit an estimate of g(omega) is developed using a
parametric statistical model from a fixed subset of omega(0), namely o
mega(1), carefully selected using the proven statistical method of cro
ss-validation combined with simple thinning out of omega(0). The estim
ated model is used in conjunction with results from future simulations
made at the reduced frequency set omega(1) to estimate g(omega) when
the circuit is run under different input conditions, providing an effi
cient method of circuit optimisation. The method is illustrated with a
n example which explores the effect of reducing frequency points for s
imulation on model accuracy. This shows the number of frequency points
can be significantly reduced while still estimating the response curv
es accurately.