| 1. |
- Bergeling, Carolina, et al.
(författare)
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Closed-form H-infinity optimal control for a class of infinite-dimensional systems
- 2020
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Ingår i: Automatica. - : Elsevier BV. - 0005-1098. ; 117
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Tidskriftsartikel (refereegranskat)abstract
- H-infinity optimal control and estimation are addressed for a class of systems governed by partial differential equations with bounded input and output operators. Diffusion equations are an important example in this class. Explicit formulas for the optimal state feedback controller as well as the optimal state estimator are given. Unlike traditional methods for H-infinity synthesis, no iteration is needed to obtain the optimal solution. Moreover, the optimal performance for both the state feedback and state estimation problems are explicitly calculated. This is shown to be useful for problems of H-infinity optimal actuator and sensor location. Furthermore, the results can be used in testing and bench-marking of general purpose algorithms for H-infinity synthesis. The results also apply to finite-dimensional systems.
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| 2. |
- Bergeling, Carolina, et al.
(författare)
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H-infinity Optimal Control for Systems with a Bottleneck Frequency
- 2021
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Ingår i: IEEE Transactions on Automatic Control. - 0018-9286. ; 66:6, s. 2732-2738
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Tidskriftsartikel (refereegranskat)abstract
- We characterize a class of systems for which the H-infinity optimal control problem can be simplified in a way that enables sparse solutions and efficient computation. For a subclass of the systems, an optimal controller can be explicitly expressed in terms of the matrices of the system's state-space representation. In many applications, the controller given by this formula, which is static, can be implemented in a decentralized or distributed fashion. Examples are temperature dynamics in buildings, water irrigation and electrical networks.
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| 3. |
- Bergeling, Carolina
(författare)
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On H-infinity Control and Large-Scale Systems
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In this thesis, a class of linear time-invariant systems is identified for which a particular type of H-infinity optimal control problem can be solved explicitly. It follows that the synthesized controller can be given on a simple explicit form. More specifically, the controller can be written in terms of the matrices of the system’s state-space representation. The result has applications in the control of large-scale systems, as well as for the control of infinite-dimensional systems, with certain properties. For the large-scale applications considered, the controller is both globally optimal as well as possesses a structure compatible with the information-structure of the system. This decentralized property of the controller is obtained without any structural constraints or regularization techniques being part of the synthesis procedure. Instead, it is a result of its particular form. Examples of applications are electrical networks, temperature dynamics in buildings and water irrigation systems.In the infinite-dimensional case, the explicitly stated controller solves the infinite-dimensional H-infinity synthesis problem directly without the need of approximation techniques. An important application is diffusion equations. Moreover, the presented results can be used for evaluation and benchmarking of general purpose algorithms for H-infinity control.The systems considered in this thesis are shown to belong to a larger class of systems for which the H-infinity optimal control problem can be translated into a static problem at a single frequency. In certain cases, the static problem can be solved through a simple least-squares argument. This procedure is what renders the simple and explicit expression of the controller previously described. Moreover, the given approach is in contrast to conventional methods to the problem of H-infinity control, as they are in general performed numerically.
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| 4. |
- Heskebeck, Frida, et al.
(författare)
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An Adaptive Approach for Task-Driven BCI Calibration
- 2021
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Konferensbidrag (refereegranskat)abstract
- One of the most significant obstacles for the everyday use of systems based on BrainComputer Interfaces (BCIs) is the tediousness of calibration. Successful improvements on calibration, particularly the time needed and the userexperience, have been made with, e.g., transfer learning, gamification, and task estimation [1, 2, 3]. Inthis work, we present an adaptive approach to BCI systems’ calibration with a model that evaluates if more calibration is needed. We inspect the model in its simplest form to showcase its versatility.
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| 5. |
- Heskebeck, Frida, et al.
(författare)
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Multi-Armed Bandits in Brain-Computer Interfaces
- 2022
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Ingår i: Frontiers in Human Neuroscience. - : Frontiers Media S.A.. - 1662-5161. ; 16
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Forskningsöversikt (refereegranskat)abstract
- The multi-armed bandit (MAB) problem models a decision-maker that optimizes its actions based on current and acquired new knowledge to maximize its reward. This type of online decision is prominent in many procedures of Brain-Computer Interfaces (BCIs) and MAB has previously been used to investigate, e.g., what mental commands to use to optimize BCI performance. However, MAB optimization in the context of BCI is still relatively unexplored, even though it has the potential to improve BCI performance during both calibration and real-time implementation. Therefore, this review aims to further describe the fruitful area of MABs to the BCI community. The review includes a background on MAB problems and standard solution methods, and interpretations related to BCI systems. Moreover, it includes state-of-the-art concepts of MAB in BCI and suggestions for future research.
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| 6. |
- Pates, Richard, et al.
(författare)
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On the Optimal Control of Relaxation Systems
- 2020
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Ingår i: 2019 IEEE 58th Conference on Decision and Control, CDC 2019. - 0743-1546 .- 2576-2370. - 9781728113999 - 9781728113982 ; 2019-December, s. 6068-6073
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Konferensbidrag (refereegranskat)abstract
- The relaxation systems are an important subclass of the passive systems that arise naturally in applications. We exploit the fact that they have highly structured state-space realisations to derive analytical solutions to some simple H-infinity type optimal control problems. The resulting controllers are also relaxation systems, and often sparse. This makes them ideal candidates for applications in large-scale problems, which we demonstrate by designing simple, sparse, electrical circuits to optimally control large inductive networks and to solve linear regression problems.
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| 7. |
- RYU, ERNEST K., et al.
(författare)
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Operator splitting performance estimation : Tight contraction factors and optimal parameter selection
- 2020
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Ingår i: SIAM Journal on Optimization. - 1052-6234. ; 30:3, s. 2251-2271
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Tidskriftsartikel (refereegranskat)abstract
- We propose a methodology for studying the performance of common splitting methods through semidefinite programming. We prove tightness of the methodology and demonstrate its value by presenting two applications of it. First, we use the methodology as a tool for computerassisted proofs to prove tight analytical contraction factors for Douglas-Rachford splitting that are likely too complicated for a human to find bare-handed. Second, we use the methodology as an algorithmic tool to computationally select the optimal splitting method parameters by solving a series of semidefinite programs.
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| 8. |
- Sandsten, Maria, et al.
(författare)
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A Novel Multitaper Reassignment Method for Estimation of Phase Synchrony
- 2021
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Ingår i: 29th European Signal Processing Conference, EUSIPCO 2021 - Proceedings. - 2219-5491. - 9789082797060 ; 2021-August, s. 2164-2168
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Konferensbidrag (refereegranskat)abstract
- The matched phase reassignment, developed to estimate phase synchrony of transient oscillatory signals, is extended into a multitaper phase reassignment (MTPR) method. The method gives perfect time-frequency localization for two transients with zero phase difference and estimates of time locations and oscillatory frequencies in low signal-to-noise ratios. For different signal-to-noise ratios between channels a suggestion of corrected reassignment vector expressions is given, resulting in minimized variance. The MTPR outperforms the matched phase reassignment as well as state-of-the-art methods, such as Pearson's linear correlation, time-frequency cross-spectrogram phase estimation and the Phase Lag Index method. An example of estimated phase differences, time locations and oscillatory frequencies of electrical signals measured from the brain is also shown.
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| 9. |
- Wilroth, Johanna, et al.
(författare)
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Improving EEG-based decoding of the locus of auditory attention through domain adaptation
- 2023
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Ingår i: Journal of Neural Engineering. - : Institute of Physics (IOP). - 1741-2560 .- 1741-2552. ; 20:6
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Tidskriftsartikel (refereegranskat)abstract
- Objective. This paper presents a novel domain adaptation (DA) framework to enhance the accuracy of electroencephalography (EEG)-based auditory attention classification, specifically for classifying the direction (left or right) of attended speech. The framework aims to improve the performances for subjects with initially low classification accuracy, overcoming challenges posed by instrumental and human factors. Limited dataset size, variations in EEG data quality due to factors such as noise, electrode misplacement or subjects, and the need for generalization across different trials, conditions and subjects necessitate the use of DA methods. By leveraging DA methods, the framework can learn from one EEG dataset and adapt to another, potentially resulting in more reliable and robust classification models. Approach. This paper focuses on investigating a DA method, based on parallel transport, for addressing the auditory attention classification problem. The EEG data utilized in this study originates from an experiment where subjects were instructed to selectively attend to one of the two spatially separated voices presented simultaneously. Main results. Significant improvement in classification accuracy was observed when poor data from one subject was transported to the domain of good data from different subjects, as compared to the baseline. The mean classification accuracy for subjects with poor data increased from 45.84% to 67.92%. Specifically, the highest achieved classification accuracy from one subject reached 83.33%, a substantial increase from the baseline accuracy of 43.33%. Significance. The findings of our study demonstrate the improved classification performances achieved through the implementation of DA methods. This brings us a step closer to leveraging EEG in neuro-steered hearing devices. © 2023 The Author(s). Published by IOP Publishing Ltd.
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