Indoor localization based on existent WiFi signal strength is becoming more and more prevalent and ubiquitous. Unfortunately, the WiFi received signal strength (RSS) is susceptible by multipath, signal attenuation, and environmental changes, which is the major challenge for accurate indoor localization. To overcome these limitations, we propose the cluster -nearest neighbor (KNN) algorithm with 5 G WiFi signal to reduce the environmental interference and improve the localization performance without additional equipment. In this paper, we propose three approaches to improve the performance of localization algorithm. For one thing, we reduce the computation effort based on the coarse localization algorithm. For another, according to the detailed analysis of the 2.4 G and 5 G signal fluctuation, we expand the real-time measurement RSS before matching the fingerprint map. More importantly, we select the optimal nearest neighbor points based on the proposed cluster KNN algorithm. We have implemented the proposed algorithm and evaluated the performance with existent popular algorithms. Experimental results demonstrate that the proposed algorithm can effectively improve localization accuracy and exhibit superior performance in terms of localization stabilization and computation effort.
The accurate relay of electrical signals within cortical networks is key to perception and cognitive function. Theoretically, it has long been proposed that temporal coordination of neuronal spiking activity controls signal transmission and behavior. However, whether and how temporally precise neuronal coordination in population activity influences perception is unknown. Here, we recorded from neuronal populations in early and mid-level visual cortex (areas V1 and V4) simultaneously to discover that the precise temporal coordination between the spiking activity of three or more cells carries information about visual perception in the absence of firing rate modulation. The accuracy of perceptual responses was correlated with high-order spiking coordination within V4, but not V1, and with feedforward coordination between V1 and V4. These results indicate that while visual stimuli are encoded in the discharge rates of neurons, perceptual accuracy is related to the temporally precise spiking coordination within and between cortical networks.
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