Item Type: | Book Section |
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Title: | Adaptive multi-modal sensors |
Creators Name: | Harrington, K.I. and Siegelmann, H.T. |
Abstract: | Compressing real-time input through bandwidth constrainedconnections has been studied within robotics, wireless sensor networks,and image processing. When there are bandwidth constraints on real-time input the amount of information to be transferred will always begreater than the amount that can be transferred per unit of time. Wepropose a system that utilizes a local diffusion process and a reinforcement learning-based memory system to establish a realtime predictionof an entire input space based upon partial observation. The proposedsystem is optimized for dealing with multi-dimension input spaces, andmaintains the ability to react to rare events. Results show the relationof loss to quality and suggest that at higher resolutions gains in qualityare possible. |
Keywords: | Sensor Network, Wireless Sensor Network, Rare Event, Sensor Chemical, Bandwidth Constraint |
Source: | Lecture Notes in Computer Science |
Series Name: | Lecture Notes in Computer Science |
Title of Book: | 50 years of artificial intelligence |
ISSN: | 0302-9743 |
ISBN: | 978-3-540-77295-8 |
Publisher: | Springer |
Volume: | 4850 |
Number: | 4850 |
Page Range: | 164-173 |
Number of Pages: | 10 |
Date: | 2007 |
Official Publication: | https://doi.org/10.1007/978-3-540-77296-5_16 |
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