scholarly journals Comparison of Direct Intersection and Sonogram Methods for Acoustic Indoor Localization of Persons

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4465
Author(s):  
Dominik Jan Schott ◽  
Addythia Saphala ◽  
Georg Fischer ◽  
Wenxin Xiong ◽  
Andrea Gabbrielli ◽  
...  
Keyword(s):  
Computational Complexity ◽  
Execution Time ◽  
High Intensity ◽  
Indoor Localization ◽  
Small Scale ◽  
Impulse Responses ◽  
Worst Case ◽  
Localization Errors ◽  
Intensity Map ◽  
Intersection Method

We discuss two methods to detect the presence and location of a person in an acoustically small-scale room and compare the performances for a simulated person in distances between 1 and 2 m. The first method is Direct Intersection, which determines a coordinate point based on the intersection of spheroids defined by observed distances of high-intensity reverberations. The second method, Sonogram analysis, overlays all channels’ room impulse responses to generate an intensity map for the observed environment. We demonstrate that the former method has lower computational complexity that almost halves the execution time in the best observed case, but about 7 times slower in the worst case compared to the Sonogram method while using 2.4 times less memory. Both approaches yield similar mean absolute localization errors between 0.3 and 0.9 m. The Direct Intersection method performs more precise in the best case, while the Sonogram method performs more robustly.

scholarly journals Comparison of Direct Intersection and Sonogram Methods for Acoustic Indoor Localization of Persons

2021 ◽  
Author(s):  
Dominik Schott ◽  
Addythia Saphala ◽  
Georg Fischer ◽  
Wenxin Xiong ◽  
Andrea Gabbrielli ◽  
...  
Keyword(s):  
High Intensity ◽  
Indoor Localization ◽  
Small Scale ◽  
Impulse Responses ◽  
Computation Complexity ◽  
Intensity Map

We discuss two methods to detect the presence and location of a person in a small-scale room and compare the performances. The first method is Direct Intersection, which determines a coordinate point based on the intersection of spheroids defined by observed distances of high-intensity reverberations. The second method, Sonogram analysis, overlays all channel’s room impulse responses to generate an intensity map for the observed environment. We demonstrate that the former method has lower computation complexity and higher accuracy for small numbers of channels, while the latter performs more robustly.

scholarly journals Linearization of multi-output logic functions by ordering of the autocorrelation values

2007 ◽  
Vol 20 (3) ◽  
pp. 479-498 ◽  
Author(s):  
Osnat Keren ◽  
Ilya Levin
Keyword(s):  
Computational Complexity ◽  
Boolean Function ◽  
Autocorrelation Function ◽  
Execution Time ◽  
Boolean Functions ◽  
Analytic Method ◽  
Implementation Cost ◽  
Initial Domain ◽  
Greedy Methods ◽  
Logic Functions

The paper deals with the problem of linear decomposition of a system of Boolean functions. A novel analytic method for linearization, by reordering the values of the autocorrelation function, is presented. The computational complexity of the linearization procedure is reduced by performing calculations directly on a subset of autocorrelation values rather than by manipulating the Boolean function in its initial domain. It is proved that unlike other greedy methods, the new technique does not increase the implementation cost. That is, it provides linearized functions with a complexity that is not greater than the complexity of the initial Boolean functions. Experimental results over standard benchmarks and random Boolean functions demonstrate the efficiency of the proposed procedure in terms of the complexity measure and the execution time.

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