This paper is concerned with the problem of robust fault detection filter design for a class of neutral-type neural networks with time-varying discrete and unbounded distributed delays. A Luenberger-type observer is designed for monitoring fault. By introducing an appropriate Lyapunov–Krasovskii functional and by using Jensen's inequality techniques to deal with its derivative, a new sufficient condition for the existence of robust fault detection filter is proposed in the form of LMIs with nonlinear constraints. To solve the nonlinear problem, a cone complementarity linearization algorithm is proposed. In addition, several numerical examples are provided to illustrate the applicability of the proposed approach. Copyright © 2012 John Wiley & Sons, Ltd.