From a practical point of view, the eventual dream is that the electronic nose will replace the K9-like tasks of detecting explosives, drugs, missing persons, diseases, etc. With this vision, electronic noses employing various materials and different detection methods are continuously being developed. Despite the strong potential of electronic noses, practical implementation has a hurdle to overcome. The K9 olfactory receptors incorporate up to ~ 220 million units. To realize a biomimetic electronic nose with a detection performance comparable to that of the K9, the number of the sensor units should be equal. To overcome this, understanding how K9's brain analyzes signals generated by its olfactory system is crucial. Signals generated by 220 million olfactory receptors are selectively and partially activated through the brain's learning process, called the neural pattern separation (NPS). The brain solves the pattern-learning and pattern-recognition problems of the signals it generates for complex and noisy stimuli in large and complex olfactory systems. To understand this incredible success, neuroscientists go beyond the hardware-based perspective and provide a convincing explanation based on the information processing system of the neural network. The patterns that are generated in the olfactory organs are very large and complex, and the internal method by which the brain computes patterns is not yet clear. Therefore, it is difficult to find the direct correlation between them. However, mechanism studies in olfactory organs provide clues to the selective actions that drive specific combinations of input signals. Here, by mimicking olfactory network dynamics, we developed the NPS, as shown in Figure below, and used it to develop a second-generation electronic nose. To demonstrate characteristics of the 2nd generation electronic nose with the NPS, we conducted studies that applied to a variety of applications, including polycyclic aromatic compound (PAH) detection, respiratory-based lung cancer diagnosis, and fruit freshness monitoring.