We propose the two implementation methods of homeostasis functionality in hardware-based spiking neural networks (SNNs). The performance of the proposed implementation methods was evaluated through the MNIST dataset classification. Both implementation methods show high performance and a significantly higher recognition rate (~92%) than when homeostasis functionality was not used (~80%). The TFT-type flash memory cells are used as synaptic devices.