Redundant Information Rejection in Sensor Localisation Using System Gramians

Author(s):  
Mladen Gibanica ◽  
Thomas J. S. Abrahamsson ◽  
Daniel C. Kammer
2000 ◽  
Author(s):  
Nicholas G. Bourbakis ◽  
Weiyi Meng

Author(s):  
Gwendolyn Rehrig ◽  
Reese A. Cullimore ◽  
John M. Henderson ◽  
Fernanda Ferreira

Abstract According to the Gricean Maxim of Quantity, speakers provide the amount of information listeners require to correctly interpret an utterance, and no more (Grice in Logic and conversation, 1975). However, speakers do tend to violate the Maxim of Quantity often, especially when the redundant information improves reference precision (Degen et al. in Psychol Rev 127(4):591–621, 2020). Redundant (non-contrastive) information may facilitate real-world search if it narrows the spatial scope under consideration, or improves target template specificity. The current study investigated whether non-contrastive modifiers that improve reference precision facilitate visual search in real-world scenes. In two visual search experiments, we compared search performance when perceptually relevant, but non-contrastive modifiers were included in the search instruction. Participants (NExp. 1 = 48, NExp. 2 = 48) searched for a unique target object following a search instruction that contained either no modifier, a location modifier (Experiment 1: on the top left, Experiment 2: on the shelf), or a color modifier (the black lamp). In Experiment 1 only, the target was located faster when the verbal instruction included either modifier, and there was an overall benefit of color modifiers in a combined analysis for scenes and conditions common to both experiments. The results suggest that violations of the Maxim of Quantity can facilitate search when the violations include task-relevant information that either augments the target template or constrains the search space, and when at least one modifier provides a highly reliable cue. Consistent with Degen et al. (2020), we conclude that listeners benefit from non-contrastive information that improves reference precision, and engage in rational reference comprehension. Significance statement This study investigated whether providing more information than someone needs to find an object in a photograph helps them to find that object more easily, even though it means they need to interpret a more complicated sentence. Before searching a scene, participants were either given information about where the object would be located in the scene, what color the object was, or were only told what object to search for. The results showed that providing additional information helped participants locate an object in an image more easily only when at least one piece of information communicated what part of the scene the object was in, which suggests that more information can be beneficial as long as that information is specific and helps the recipient achieve a goal. We conclude that people will pay attention to redundant information when it supports their task. In practice, our results suggest that instructions in other contexts (e.g., real-world navigation, using a smartphone app, prescription instructions, etc.) can benefit from the inclusion of what appears to be redundant information.


2011 ◽  
Vol 105-107 ◽  
pp. 1851-1855 ◽  
Author(s):  
Li Bin Lu ◽  
Ding Xin Chen ◽  
Guo Dong Jin ◽  
Rong Ming Li ◽  
Ying Jie Gao

To study the problem of high precision, the reason why error appears in the ultrasonic positioning process is analyzed. To decrease the effect of error, this paper raises the algorithm of curve-fitting extrapolation and redundant information fusion. The experiment and contrast on precision between this algorithm and other classical ones demonstrate that, the new algorithm could effectively control measurement errors and raise the precision of ultrasonic positioning.


2021 ◽  
pp. 1-15
Author(s):  
Rongde Lin ◽  
Jinjin Li ◽  
Dongxiao Chen ◽  
Jianxin Huang ◽  
Yingsheng Chen

Fuzzy covering rough set model is a popular and important theoretical tool for computation of uncertainty, and provides an effective approach for attribute reduction. However, attribute reductions derived directly from fuzzy lower or upper approximations actually still occupy large of redundant information, which leads to a lower ratio of attribute-reduced. This paper introduces a kind of parametric observation sets on the approximations, and further proposes so called parametric observational-consistency, which is applied to attribute reduction in fuzzy multi-covering decision systems. Then the related discernibility matrix is developed to provide a way of attribute reduction. In addition, for multiple observational parameters, this article also introduces a recursive method to gradually construct the multiple discernibility matrix by composing the refined discernibility matrix and incremental discernibility matrix based on previous ones. In such case, an attribute reduction algorithm is proposed. Finally, experiments are used to demonstrate the feasibility and effectiveness of our proposed method.


2022 ◽  
Vol 22 (2) ◽  
pp. 1-15
Author(s):  
Tu N. Nguyen ◽  
Sherali Zeadally

Conventional data collection methods that use Wireless Sensor Networks (WSNs) suffer from disadvantages such as deployment location limitation, geographical distance, as well as high construction and deployment costs of WSNs. Recently, various efforts have been promoting mobile crowd-sensing (such as a community with people using mobile devices) as a way to collect data based on existing resources. A Mobile Crowd-Sensing System can be considered as a Cyber-Physical System (CPS), because it allows people with mobile devices to collect and supply data to CPSs’ centers. In practical mobile crowd-sensing applications, due to limited budgets for the different expenditure categories in the system, it is necessary to minimize the collection of redundant information to save more resources for the investor. We study the problem of selecting participants in Mobile Crowd-Sensing Systems without redundant information such that the number of users is minimized and the number of records (events) reported by users is maximized, also known as the Participant-Report-Incident Redundant Avoidance (PRIRA) problem. We propose a new approximation algorithm, called the Maximum-Participant-Report Algorithm (MPRA) to solve the PRIRA problem. Through rigorous theoretical analysis and experimentation, we demonstrate that our proposed method performs well within reasonable bounds of computational complexity.


Author(s):  
D.T. Stuss ◽  
L.L. Stethem ◽  
T.W. Picton ◽  
E.E. Leech ◽  
G. Pelchat

ABSTRACT:The effects of traumatic brain injury (TBI) and aging were compared on tests of simple and complex reaction time (RT). Simple RT was not significantly affected by aging or TBI. TBI patients, however, tended to be slower on Simple RT tasks, and had a larger standard deviation. Individuals over age 60 and patients of any age with TBI demonstrated slower RT with choice RT tests. In addition, both groups (those over 60 and TBI patients) were less able than other groups to inhibit the processing of redundant information. For the TBI patients, this occurred primarily on reassessment. These results suggest that the deficit in both aging and TBI is not only a generalized neuronal slowing but a more specific impairment in attentional control processes, exhibited as a deficit in focused attention.


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