An Accurate Sparse-Matrix Semisymbolic Algorithm for Analyzing Distributed Microwave Circuits

An optimal pivoting strategy for the reduction algorithm transforming the general eigenvalue problem to the standard one is presented for both full- and sparse-matrix procedures. The algorithm increases the precision of the semisymbolic analysis especially for the large-scale microwave circuits. The accuracy is furthermore increased using longer numerical data. First, the long double precision is utilized. Further, the application of a suitable multiple-precision arithmetic library is suggested. Finally, using the longer numerical data to eliminate possible imprecision of the multiple eigenvalues is evaluated. The algorithm is demonstrated by estimating the frequency of a distributed microwave oscillator, and by estimating the bandwidth of a distributed microwave amplifier.