Complex-valued Adaptive System Identification via Low-Rank Tensor Decomposition

Machine learning (ML) and tensor-based methods have been of significant interest for the scientific community for the last few decades. In a previous work we presented a novel tensor-based system identification framework to ease the computational burden of tensor-only architectures while still being able to achieve exceptionally good performance. However, the derived approach only allows to process real-valued problems and is therefore not directly applicable on a wide range of signal processing and communications problems, which often deal with complex-valued systems. In this work we therefore derive two new architectures to allow the processing of complex-valued signals, and show that these extensions are able to surpass the trivial, complex-valued extension of the original architecture in terms of performance, while only requiring a slight overhead in computational resources to allow for complex-valued operations

Enhanced Nonlinear System Identification by Interpolating Low-Rank Tensors

Function approximation from input and output data is one of the most investigated problems in signal processing. This problem has been tackled with various signal processing and machine learning methods. Although tensors have a rich history upon numerous disciplines, tensor-based estimation has recently become of particular interest in system identification. In this paper we focus on the problem of adaptive nonlinear system identification solved with interpolated tensor methods. We introduce three novel approaches where we combine the existing tensor-based estimation techniques with multidimensional linear interpolation. To keep the reduced complexity, we stick to the concept where the algorithms employ a Wiener or Hammerstein structure and the tensors are combined with the well-known LMS algorithm. The update of the tensor is based on a stochastic gradient decent concept. Moreover, an appropriate step size normalization for the update of the tensors and the LMS supports the convergence. Finally, in several experiments we show that the proposed algorithms almost always clearly outperform the state-of-the-art methods with lower or comparable complexity.Comment: 12 pages, 4 figures, 3 table

Adaptive System Identification via Low-Rank Tensor Decompositi

Tensor-based estimation has been of particular interest of the scientific community for several years now. While showing promising results on system estimation and other tasks, one big downside is the tremendous amount of computational power and memory required – especially during training – to achieve satisfactory performance. We present a novel framework for different classes of nonlinear systems, that allows to significantly reduce the complexity by introducing a least-mean-squares block before, after, or between tensors to reduce the necessary dimensions and rank required to model a given system. Our simulations show promising results that outperform traditional tensor models, and achieve equal performance to comparable algorithms for all problems considered while requiring significantly less operations per time step than either of the state-of-the-art architectures

Isolation in Globalizing Academic Fields: A Collaborative Autoethnography of Early Career Researchers

This study examines academic isolation – an involuntary perceived separation from the academic field to which one aspires to belong, associated with a perceived lack of agency in terms of one’s engagement with the field – as a key challenge for researchers in increasingly globalized academic careers. While prior research describes early career researchers’ isolation in their institutions, we theorize early career researchers’ isolation in their academic fields and reveal how they attempt to mitigate isolation to improve their career prospects. Using a collaborative autoethnographic approach, we generate and analyze a dataset focused on the experiences of ten early career researchers in a globalizing business academic field known as Consumer Culture Theory. We identify bricolage practices, polycentric governance practices, and integration mechanisms that work to enhance early career researchers’ perceptions of agency and consequently mitigate their academic isolation. Our findings extend discussions on isolation and its role in new academic careers. Early career researchers, in particular, can benefit from a deeper understanding of practices that can enable them to mitigate isolation and reclaim agency as they engage with global academic fields

SecUAV - A Uni_ed testbed for the evaluation of secure state estimators

This TFM is focused on secure estimation, specifically on detect and counteract attacks on sensor networks by means of signal processing/estimation. The project will start with a review of state of the art secure estimators, to continue with the implementation of some algorithms in order to compare differents systems. Althought the project is done at UPC, it considers the collaboration with the Networked & Embedded Systems Laboratory (NESL) at the University of California at Los Angeles (UCLA).Rapidly evolving technology and tight coupling of physical sensors and actuation with the system behind it in Cyber Physical Systems (CPS) have opened up new forms of security vulnerabilities to adversaries. These new types of attacks on the physical (PHY) layer can be used to drive the system in an undesired, unstable state which could ultimately resolve in life-threatening consequences for users. This new research-area has gained traction in the CPS community recently, but a feasible solution has yet to be found. One problem with the current approach of proposing algorithms and counter-measures against such attacks is, that it can be hard to compare different works in terms of effectiveness and computational cost as every research group has different ways of providing results. This work introduces SecUAV, common testbed for the CPS community. SecUAV utilizes OpenUAV, an open-source UAV simulator, for providing a common testbed for the fair evaluation of secure state estimation algorithms. This is achieved by expanding the already existing functionality with a framework allowing to simulate different kinds of attacks and to deploy different secure CPS algorithms. The feasibility of SecUAV is demonstrated by deploying three works in it, and comparing the resulting data in a fair manner. One of the studies algorithms, ReCaP [1], has been developed and evaluated by SecUAV during the work on this thesis

Success and complication rate of miniscrew assisted non-surgical palatal expansion in adults - a consecutive study using a novel force-controlled polycyclic activation protocol.

INTRODUCTION Bone-borne miniscrew assisted palatal expansion (MAPE) is a common technique to improve maxillary transverse deficiency in young adolescents. Adult patients usually present a challenge, as they often require additional surgical assisted maxillary expansion (SARPE). There is still no clear statement about non-surgical expansion in adult patients using this technique. The aim of this study was to evaluate the success and complication rate of non-surgical palatal expansion in adults utilizing MAPE with a novel force-controlled polycyclic expansion protocol (FCPC). METHODS This consecutive study consisted of 33 adult patients with an average age of 29.1 ± 10.2 years (min. 18 years, max. 58 years), including one dropout patient. First, four miniscrews were inserted and after 12-weeks latency, the expander was placed and the FCPC protocol was applied (MAPE group). In case of missing expansion, a SARPE was performed (SARPE group). After maximum expansion, a cone beam CT was made and widening of the midpalatal suture was measured. The outcome variables were successful non-surgical expansion and, with sample size power above 80%, the odds of failed non-surgical expansion and associated complications were evaluated. The primary predictor variable was age. Statistical analysis was performed using R (Version 3.1) to calculate power, to construct various models for measuring the odds of requiring surgical intervention/complications, and others. RESULTS Successful non-surgical expansion was achieved in 27 patients (84.4%), ranging from 18 to 49 years. Mean age differed significantly between both groups (26.8 ± 8.2 years vs. 41.3 ± 9.9 years; p < 0.001). Mean expansion at the anterior and posterior palate for the MAPE group was 5.4 ± 1.5 mm and 2.5 ± 1.1 mm, respectively. Among these subjects' complications were observed in 18.5%. Age significantly increased the odds of complications (p = 0.019). CONCLUSIONS 1. The success rate of MAPE among individuals aged 18 to 49 years was 84.4%. 2. A V-shaped expansion pattern in the antero-posterior dimension was mostly observed. 3. Complications were significantly associated with age. 4. A careful expansion protocol seems to be beneficial to prevent unfavorable results in adult patients. TRIAL REGISTRATION Consecutive cohort study, Review Board No. EK-2-2014/0016

Osteoporosis and bisphosphonates-related osteonecrosis of the jaw: Not just a sporadic coincidence - a multi-centre study

Bisphosphonates (BPs) are powerful drugs that inhibit bone metabolism. Adverse side effects are rare but potentially severe such as bisphosphonate-related osteonecrosis of the jaw (BRONJ). To date, research has primarily focused on the development and progression of BRONJ in cancer patients with bone metastasis, who have received high dosages of BPs intravenously. However, a potential dilemma may arise from a far larger cohort, namely the millions of osteoporosis patients on long-term oral BP therapy