A Globally Coupled Map (GCM) model is a network of chaotic elements that are globally coupled with each other. We have previously proposed an associative memory system based on GCM, which has a better ability than the Hopfield network. This result indicates that the dynamics of our system is more efficient than that of the Hopfield network. However, even in our system, spurious memories, i.e., system's equilibria that do not correspond to any of proper memories, do exist. In this paper, we propose a modified associative memory system, in which spurious memories are noticeably reduced. This is achieved by modifying the chaotic dynamics of the system. With this improvement, our system's memory capacity and basin volumes are expanded a great deal. Some experimental results in comparison with those of a neural network employing a nonmonotonic output function are also shown. Keywords: chaos, globally coupled map, associative memory, nonmonotonic dynamics, spurious memory 2 1 Introduction...