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This brief studies the design of complex-valued variable digital filters (CVDFs) and their applications to the efficient arbitrary sample rate conversion for complex signals. The design of CVDFs using either the minimax or least-squares criteria is formulated as a convex optimization problem and solved using the second-order cone programming (SOCP). In addition, linear and convex quadratic inequality constraints can be readily incorporated. Design examples are given to demonstrate the effectiveness of the proposed approach.