Various memory devices have been proposed for implementing synapse devices in neuromorphic systems. In this letter, an AND flash array based on charge trap flash (CTF) memory was proposed. CTF-based synapse devices are particularly suitable for off-chip learning applications because they have excellent reliability and stable multi-level operation characteristics. In addition, we proposed a method to implement convolutional neural networks in the proposed array, and performed system-level simulation using the characteristics of the fabricated device. Finally, we investigated the accuracy degradation of the neuromorphic system related to data retention and proposed a multiple cell mapping scheme to address this degradation issue.