# An Improved Biomimetic Olfactory Model and Its Application in Traffic Sign Recognition
## 2 The KIII Model  
The KIII model is constructed based on the anatomical structure of the entire anterior olfactory neural pathway, and it exhibits a well-defined correspondence with the structure of the olfactory system. The K-series models consist of K0, KI, KII, and KIII, with K0 serving as the fundamental module. The KI model is composed of two K0 models, and the KII model is composed of two KI models. The K0, KI, and KII models are interconnected in a feedforward and delayed feedback manner to form the KIII model. As shown in Figure 1, the complete KIII model is divided into five layers: the periglomerular cell (PG) layer, the olfactory bulb (OB) layer, the anterior olfactory nucleus (AON) layer, the prepyriform cortex (PC) layer, and the external capsule (EC) layer. The following is the topological structure of the KIII model:  
In the Figure 1, symbols and labels are used to represent different cell types and neuronal layers to provide a better description of the composition and functionality of the olfactory system. Specifically, the symbol '+' denotes excitation, while the symbol '-' denotes inhibition. 'R' is used to represent olfactory receptor cells responsible for perceiving and receiving odor information. 'P' represents the periglomerular cells connecting the olfactory bulb, which are part of the OB (olfactory bulb) layer. 'M' and 'G' denote excitatory mitral cells and inhibitory granule cells, respectively, together forming the KII model, which simulates the OB layer. Inhibitory 'I' and excitatory 'E' cells constitute the KII model, corresponding to the anterior olfactory nucleus (AON) layer. Additionally, inhibitory 'B' and excitatory 'A' cells form the KII model, corresponding to the prepyriform cortex (PC). 'C' represents deep pyramidal cells [6; 13; 14; 15].  
In the KIII model, each 'R' represents a K0 model, and 'n' parallel 'R' units constitute the n-channel input of the KIII model. The periglomerular cells 'P' preprocess signals from olfactory receptors 'R'. Mitral cells 'M' in the olfactory bulb layer (OB) receive signals from both periglomerular cells 'P' and olfactory receptors 'R' and transmit information to granule cells 'G'. Mitral cells 'M' excite granule cells 'G', while granule cells 'G' inhibit mitral cells 'M', forming a negative feedback oscillatory neural loop. After processing in the olfactory bulb layer OB, mitral cells 'M' transmit information to the anterior olfactory nucleus (AON) and the prepyriform cortex (PC) through the lateral olfactory tract (LOT). The anterior olfactory nucleus (AON) and the prepyriform cortex (PC) also contain excitatory neurons 'E' and 'A', as well as inhibitory neurons 'I' and 'B', forming similar oscillatory loops. The output signals from the prepyriform cortex (PC) reach the external capsule (EC) and provide feedback to the AON layer, OB layer, and PG layer through the 'Di' feedback mechanism. The oscillatory characteristics and negative feedback mechanism of these neural loops provide unique dynamic properties for odor signal processing.  
In the KIII model, the dataset is initially divided into training and testing sets in proportion. After preprocessing, the data is transformed into feature vectors and subsequently fed into 'N' channels. During this process, Hebbian learning is applied to extract the OB layer matrix, compute clustering centers for each class, and determine the weight parameters for each layer, which are then saved. Testing samples also undergo a similar process, leading to the calculation of a clustering center. In the decision layer, a similarity metric algorithm is employed to compare the testing center with the saved clustering centers, ultimately yielding the predicted class results. The overall process of training and testing in the KIII model is depicted in Figure 2.  
Figure 1: KIII model topology.