YMBOLIC ANALYSIS for analog integrated circuits has received quite some research interest over the last ten years. In general, techniques for the analysis of electronic circuits can be divided in two main categories: 1) numerical simulation as used in the well-known SPICE program, where the values of all circuit elements are given and the circuit response to an input excitation is calculated in numerical form and 2) symbolic analysis where the circuit elements are represented by symbols and the desired network characteristic is derived as an analytic expression. Very much like designers do by hand analysis, the complexity of these analytic expressions is controlled using sophisticated symbolic approximation techniques, which simplify the equations by discarding insignificant contributions. Although numerical simulators today are very powerful, they basically serve to verify the circuit performance of an already sized circuit. In order to understand and predict the behavior of an unsized circuit, however, symbolic analysis techniques are more appropriate, provided that they can generate interpretable expressions. In recent years, large research progress has been achieved to develop better approximation techniques that can handle realistically large analog circuits of the complexity of, for instance, the entire 741 opamp in acceptable CPU times. Besides serving as an interactive design aid, symbolic analysis techniques can be also used for many other applications which involve the repeated evaluation of a circuit’s characteristics, such as in fault diagnosis, behavioral model generation, statistical circuit analysis, etc. This special section of the IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS—II contains a number of research papers that