首页|New Robotics Study Results from Nanchang University Described (A New Super-predefined-time Convergence and Noise-tolerant Rnn for Solving Time-variant Linear Matrix-vector Inequality In Noisy Environment and Its Application To Robot Arm)
New Robotics Study Results from Nanchang University Described (A New Super-predefined-time Convergence and Noise-tolerant Rnn for Solving Time-variant Linear Matrix-vector Inequality In Noisy Environment and Its Application To Robot Arm)
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NETL
NSTL
Springer Nature
2024 FEB 02 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Robotics have been published. According to news originating from Nanchang, People’s Republic of China, by NewsRx correspondents, research stated, “Recurrent neural networks (RNNs) are excellent solvers for time-variant linear matrix-vector inequality (TVLMVI). However, it is difficult for traditional RNNs to track the theoretical solution of TVLMVI under non-ideal conditions [e.g., noisy environment].” Financial support for this research came from National Natural Science Foundation of China (NSFC).
NanchangPeople’s Republic of ChinaAsiaEmerging Tech- nologiesMachine LearningRobotRoboticsNanchang University
NETL
NSTL
Springer Nature
