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- W2108142446 abstract "Whether interacting with a Collaborative Virtual Environment, or CVE, locally or one networked across the Internet, any delay in the system can lead to a reduced sense of immersion. Input sensor delay and network delay are two common problems in CVE design that can be overcome with the application of prediction algorithms to the system. The purpose of this experiment was to assess the quality of feed forward back propagation neural networks in predicting natural avatar arm movement used in a CVE. In addition the experiment attempted to find the bounds for precise neural network prediction. The results show many different combinations of back propagation neural network topologies are capable of predicting up to 400 ms of human arm movements relatively accurately." @default.
- W2108142446 created "2016-06-24" @default.
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- W2108142446 date "2008-01-01" @default.
- W2108142446 modified "2023-09-26" @default.
- W2108142446 title "Neural Networks for Human Arm Movement Prediction in CVEs" @default.
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