This paper deals with a novel active filter synthesis method using artificial intelligence (AI). The AI-based synthesis methodology uses original analog circuit representation performed by a Prolog backward-chaining inference mechanism. Circuit representation is specified as an analog circuit language to describe filter topologies, performance characteristics, and subcircuits. Synthesis is organized as a Prolog searching program based on backward-chaining strategy to transform input specifications into an appropriate filter structure. The Prolog program performs symbolic equation transformations to proper filter transfer characteristics. The proposed synthesis methodology has been developed for integrated continuous-time filter structures using operational transconductance amplifiers and capacitors to realize tunable and active C filters. A synthesis program has been implemented in Turbo Prolog on an IBM PC AT computer, and a filter example is presented demonstrating the use of the program.