An electronic nose system for herbs clcissification is designed and tested. The system uses the Figaro TGS800 series sensors with an integrated heating element. The testing of the system was carried out using diíferent types of herbs where it was proved to be successful in classifying them into diíferent classes [10, 11]. Database-based software was designed to interface the built hardware and to process the electronic nose signals before being classified.
The design, build and test of a re-programmable neural switch (RNS) are carried out. The function of such a switch is to operate as a synaptic processor behaving in an adaptive manner and suitable to be used as a compact programmable device with other artificial neural network hardware. Interaction between constituent materials forming the switch is discussed and carrier interaction during the Programming cycles is explained. Programmability of the switch is proved to be bi-directional and reversible with hysteresis effect which is due to excess charge storage.