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Correlations in state space can cause sub-optimal adaptation of optimal feedback control models

Jonathan Aprasoff, Opher Donchin
2011 Journal of Computational Neuroscience  
However, since the state space for control of real movements is far more complex than in our simple simulations, the effects of correlations on re-adaptation of the controller from the forward model cannot  ...  However, they also show that re-optimizing the controller from the forward model can be sub-optimal.  ...  .: Helped in the design of the simulations, contributed to the mathematical derivations, did part of the programming, and edited the paper.  ... 
doi:10.1007/s10827-011-0350-z pmid:21792671 pmcid:PMC3304072 fatcat:uhed3tfanrbuxdkz2hv3crmsja

Control Theoretic Approach to Platform Optimization using HMM [chapter]

Rahul Khanna, Huaping Liu, Mariette Aw
2011 Hidden Markov Models, Theory and Applications  
A false positive trigger acts as a feedback for retraining the model.  ...  A functional approach would correlate the system observations (using usage and activity profile) and state transitions to predict the most probable state. 293 Control Theoretic Approach to Platform Optimization  ...  The sub-optimal states need to be predicted well in advance such that corrective actions can be employed within an opportunistic window of time.  ... 
doi:10.5772/15038 fatcat:angt6jtebbh3tjv5fa5eorn7tu

Stochastic Control of Event-Driven Feedback in Multiantenna Interference Channels

Kaibin Huang, Vincent K. N. Lau, Dongku Kim
2011 IEEE Transactions on Signal Processing  
For high mobility and considering the sphere-cap-quantized-CSI model, the optimal feedback-control policy is shown to perform water-filling in time, where the number of feedback bits increases logarithmically  ...  The deployment of this technique requires channel-state information (CSI) feedback from each receiver to all interferers, resulting in substantial network overhead.  ...  The Structure of the Optimal Feedback-Control Policy To simplify the solution of (15), we consider the spherecap-quantized-CSI model in Example 1, resulting in the optimal feedback-control policy of the  ... 
doi:10.1109/tsp.2011.2165063 fatcat:cazxfiytszgrdne3lqrf2juooa

Interfacing With the Computational Brain

A. Jackson, E. E. Fetz
2011 IEEE transactions on neural systems and rehabilitation engineering  
Recent experiments reveal how volitional activity in the motor system combines with sensory feedback to shape neural representations and drives adaptation of behavior.  ...  noise and internal models for predictive control.  ...  His scientific interests include the neural mechanisms of motor control, cortical plasticity and spinal cord physiology.  ... 
doi:10.1109/tnsre.2011.2158586 pmid:21659037 pmcid:PMC3372096 fatcat:bc55bvizdvgn7ag7dk7pqc67j4

Enhancing E-commerce Recommender System Adaptability with Online Deep Controllable Learning-To-Rank

Anxiang Zeng, Han Yu, Hua-Lin He, Yabo Ni, Yongliang Li, Jingren Zhou, Chunyan Miao
2021 AAAI Conference on Artificial Intelligence  
It enhances the feedback controller in LTR with multiobjective optimization so as to maximize different objectives under constraints.  ...  Recently, the focus of research has shifted from single objective optimization to multi-objective optimization in the face of changing business requirements.  ...  Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not reflect the views of National Research Foundation, Singapore.  ... 
dblp:conf/aaai/ZengYHNLZM21 fatcat:q27eejrzurdh5htajjeovrky4m

Rate-Maximizing OFDM Pilot Patterns for UAV Communications in Nonstationary A2G Channels [article]

Raghunandan M. Rao, Vuk Marojevic, Jeffrey H. Reed
2018 arXiv   pre-print
The receiver solves this rate-maximization problem, and the optimal pilot spacing and power are explicitly fed back to the transmitter to adapt to the time-varying channel statistics in an air-to-ground  ...  We show the enhanced throughput performance of this scheme for UAV communications in sub-6 GHz bands.  ...  of the the optimal parameters V o to facilitate pilot adaptation as shown in Fig. 2 .  ... 
arXiv:1805.08896v1 fatcat:p3kb6ewzergxxgu3yfdksjskri

Hierarchical Optimal Control Method for Controlling Self-Organized Networks with Light-Weight Cost

Naomi Kuze, Daichi Kominami, Kenji Kashima, Tomoaki Hashimoto, Masayuki Murata
2015 2015 IEEE Global Communications Conference (GLOBECOM)  
Specifically, biological systems can evolve according to their habitats, and moreover, can adapt flexibly to environmental changes including unexpected ones.  ...  Temporary expansions of systems according to additional requirements for new services and applications are insufficient for retaining the durability and controllability of systems.  ...  dynamics in the form of the state space model.  ... 
doi:10.1109/glocom.2015.7417665 fatcat:tzsmpq4lwjg6dmm3xzbh4a2mfu

Hierarchical Optimal Control Method for Controlling Self-Organized Networks with Light-Weight Cost

Naomi Kuze, Daichi Kominami, Kenji Kashima, Tomoaki Hashimoto, Masayuki Murata
2014 2015 IEEE Global Communications Conference (GLOBECOM)  
Specifically, biological systems can evolve according to their habitats, and moreover, can adapt flexibly to environmental changes including unexpected ones.  ...  Temporary expansions of systems according to additional requirements for new services and applications are insufficient for retaining the durability and controllability of systems.  ...  dynamics in the form of the state space model.  ... 
doi:10.1109/glocom.2014.7417665 dblp:conf/globecom/KuzeKKHM15 fatcat:hd7ebqzaq5bopj3yminfzbqzwu

A Simple 3-Parameter Model for Examining Adaptation in Speech and Voice Production

Elaine Kearney, Alfonso Nieto-Castañón, Hasini R. Weerathunge, Riccardo Falsini, Ayoub Daliri, Defne Abur, Kirrie J. Ballard, Soo-Eun Chang, Sara-Ching Chao, Elizabeth S. Heller Murray, Terri L. Scott, Frank H. Guenther
2020 Frontiers in Psychology  
The model is a simplified version of the DIVA model, an adaptive neural network model of speech motor control.  ...  The model is tested through computer simulations that identify optimal model fits to six existing sensorimotor adaptation datasets.  ...  SUPPLEMENTARY MATERIAL The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2019. 02995/full#supplementary-material  ... 
doi:10.3389/fpsyg.2019.02995 pmid:32038381 pmcid:PMC6985569 fatcat:g4ypaow7c5hqdccd5ze7v2e3ge

Flight Controller and Low-Cost Test Environment for a Simulated Helicopter

Martin C. Terblanche, Kenneth R. Uren, George van Schoor
2014 IFAC Proceedings Volumes  
The identified state space model shows a good measure of fit compared to the simulator's flight data.  ...  A grey-box time-domain system identification method is used to estimate a linear state space model that operates in hover mode.  ...  or recommendations expressed in any publication generated by the NRF supported research are that of the authors, and that the NRF accepts no liability whatsoever in this regard.  ... 
doi:10.3182/20140824-6-za-1003.02194 fatcat:zgbgccryczfkni57drficzef74

On Channel Correlation Based Scheduling and Signalling for MIMO-OFDMA Downlink

Andreas Ibing, Holger Boche, Philipp Otto
2011 2011 IEEE 73rd Vehicular Technology Conference (VTC Spring)  
Different schemes of correlation feedback signalling are discussed in terms of (time-variant) expected throughput.  ...  The scheme is shown to improve adaptive choice of transmission parameters and to avoid mis-adaptation due to control lag.  ...  A different cause of changing correlation can be variation of the spectrum shape due to alterations of reflectors and scatterers in the channel (e.g. passing cars, trains).  ... 
doi:10.1109/vetecs.2011.5956189 dblp:conf/vtc/IbingBO11 fatcat:o2d4vjo3knhgxlnvspszom2zy4

Supplementary Material from A spiking neural model of adaptive arm control

Travis DeWolf, Terrence C. Stewart, Jean-Jacques Slotine, Chris Eliasmith
2016 Figshare  
Further details of the paper, including: comparison to past work, predictions made, methods and materials, model architecture, and neural analysis.  ...  S3.3 Nonlinear adaptive control in neurons In nonlinear adaptive control, it is assumed that system performance errors are a result of sub-optimal control signals, caused by inaccuracies in the controller's  ...  In [42] , a framing of the motor control system in terms of optimal feedback control theory is presented. There are two main ideas exploited in optimal feedback control theory.  ... 
doi:10.6084/m9.figshare.4239737.v1 fatcat:7czrwgt4jjec7cxia5bm4gdzae

Event-Driven Optimal Feedback Control for Multiantenna Beamforming

Kaibin Huang, Vincent K. N. Lau, Dongku Kim
2010 IEEE Transactions on Signal Processing  
The required feedback of channel state information (CSI) can potentially result in excessive overhead especially for high mobility or many antennas.  ...  This result holds regardless of whether the controller's state space is discretized or continuous.  ...  in the spaces of g and z can be adjusted to yield a better approximation of the optimal policy for the continuous state space.  ... 
doi:10.1109/tsp.2010.2045426 fatcat:bqd7otx34ffw5lazfzwyx6xvgy

A Broadcast Scheme for MIMO Systems with Channel State Information at the Transmitter

I. HWANG, C. YOU, D. KIM, Y. KIM, V. TAROKH
2008 IEICE transactions on communications  
The essence of channel-adaptive transmission is to feedback channel state information (CSI) from receiver to transmitter so that the transmitter can adjust the parameters based on the feedback information  ...  Normally, imperfect CSI is incurred at two places, channel estimation and feedback. Noisy channel estimation can cause random interference in the detection which can not be eliminated.  ... 
doi:10.1093/ietcom/e91-b.2.613 fatcat:dwv3x6s5ebed7caq6h5drrcfim

Supplementary Material from A spiking neural model of adaptive arm control

Travis DeWolf, Terrence C. Stewart, Jean-Jacques Slotine, Chris Eliasmith
2016 Figshare  
Further details of the paper, including: comparison to past work, predictions made, methods and materials, model architecture, and neural analysis.  ...  S3.3 Nonlinear adaptive control in neurons In nonlinear adaptive control, it is assumed that system performance errors are a result of sub-optimal control signals, caused by inaccuracies in the controller's  ...  In [42] , a framing of the motor control system in terms of optimal feedback control theory is presented. There are two main ideas exploited in optimal feedback control theory.  ... 
doi:10.6084/m9.figshare.4239737 fatcat:bhlhpz6bizh73ghrkd7knkicx4
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