A new algorithm for solving a set of canonical piecewise-linear equati
ons with linear partitions is presented. When solving a set of linear
equations repeatedly, the proposed algorithm compares images of next-g
uess candidates with those of the actual solution while minimizing the
computational overhead and finds the best next-guess which is closest
to the actual solution. Analysis of test circuits shows that the prop
osed algorithm requires 8 to 20 times fewer iterations and 5 to 10 tim
es less CPU time than the Katzenelson algorithm. Improved results vary
depending on the size of the test circuits. The experimental results
also show that the efficiency of the proposed algorithm over the Katze
nelson algorithm increases as the number of the piecewise-linear regio
ns of the resistive networks is increased.