Olfactory stimuli are represented in a high-dimensional space by neural networks of the olfactory system. While a number of studies have illustrated the importance of inhibitory networks within the olfactory bulb or the antennal lobe for the shaping and processing of olfactory information, it is not clear how exactly these inhibitory networks are organized to provide filtering and contrast enhancement capabilities. In this work the aim is to study the topology of the proposed networks by using software simulations and hardware implementation. While we can study the dependence of the activity on each parameter of the theoretical models with the simulations, it is important to understand whether the models can be used in robotic applications for real-time odor recognition. We present the results of a linear simulation, a spiking simulation with I&F neurons and a real-time hardware emulation using neuromorphic VLSI chips.