This paper presents a systematic methodology for the generation of high-level performance models for analog component blocks. The transistor sizes of the circuit-level implementations of the component
blocks along with a set of geometry constraints applied over them define the sample space. A Halton
sequence generator is used as a sampling algorithm. Performance data are generated by simulating
each sampled circuit configuration through SPICE. Least squares support vector machine (LS-SVM) is
used as a regression function. Optimal values of the model hyper parameters are determined through a
grid search-based technique and a genetic algorithm- (GA-) based technique. The high-level models of the
individual component blocks are combined analytically to construct the high-level model of a complete
system. The constructed performance models have been used to implement a GA-based high-level topology
sizing process. The advantages of the present methodology are that the constructed models are accurate
with respect to real circuit-level simulation results, fast to evaluate, and have a good generalization
ability. In addition, the model construction time is low and the construction process does not require
any detailed knowledge of circuit design. The entire methodology has been demonstrated with a set
of numerical results.