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2021 International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design, SMACD 2021 and 16th Conference on PhD Research in Microelectronics and Electronics, PRIME 2021

作者： Chatterjee, Saikat Rückert, Ulrich Cognitronics and Sensor Systems Group CITEC Bielefeld University 33619 Germany

ISBN: (纸本)9783800755899

This paper presents a resource efficient level shifter circuit, which is capable of converting input voltages below subthreshold to above threshold voltages, making it suitable for ultra low power applications such as wireless sensor networks, biomedical implants, environmental sensors, to name a few. The proposed circuit topology has two stages. The first stage comprises of a Wilson current mirror, whereas the second stage has a cross coupled PMOS circuit. The two staged topology helps to overcome the challenges of deep nano process, when operated with ultra low input supply voltage. The circuit presented here, is implemented in 28 nm FDSOI technology from ST Microelectronics. The proposed level shifter is capable of converting an input voltage as low as 150 mV to 1 V. The static power consumption is measured to be 100 pW, when the circuit is operated with the minimum possible input supply and operational frequency of 500 kHz. © VDE VERLAG GMBH.

关键词： Topology

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Bidirectional UWB Localization: A Review on an Elastic Positioning Scheme for GNSS-deprived Zones

arXiv

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arXiv 2023年

作者： Sang, Cung Lian Adams, Michael Hesse, Marc Rückert, Ulrich Cognitronics and Sensor Systems Group CITEC Bielefeld University Inspiration 1 Bielefeld33619 Germany

A bidirectional Ultra-Wideband (UWB) localization scheme is one of the three widely adopted design integration processes commonly used in time-based UWB positioning systems. The key property of bidirectional UWB localization is its ability to serve both navigation and tracking tasks within a single localization scheme on demand. Traditionally, navigation and tracking in wireless localization systems were treated as separate entities due to distinct applicable use-cases and methodological needs in each implementation process. Therefore, the ability to flexibly or elastically combine two unique positioning perspectives (navigation and tracking) within a single scheme can be regarded as a paradigm shift in the way location-based services are conventionally observed. This article reviews the mentioned bidirectional UWB localization from the perspective of a flexible and versatile positioning topology and highlights its potential in the field. In this regard, the article comprehensively describes the complete system model of the bidirectional UWB localization scheme using modular processes. It also discusses the demonstrative evaluation of two system integration processes and conducts a SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis of the scheme. Furthermore, the prospect of the presented bidirectional localization scheme for achieving precise location estimation in 5G/6G wireless mobile networks, as well as in Wi-Fi fine-time measurement-based positioning systems was briefly discussed. © 2023, CC BY.

关键词： Topology

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A Comparative Study of UWB-based True-Range Positioning Algorithms using Experimental Data

A Comparative Study of UWB-based True-Range Positioning Algo...

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Workshop on Positioning, Navigation and Communication, WPNC

作者： Cung Lian Sang Michael Adams Marc Hesse Timm Hörmann Timo Korthals Ulrich Rückert Cognitronics and Sensor Systems Group CITEC Bielefeld Univeristy Bielefeld Germany

In this paper, we analyze five true-range positioning algorithms for UWB-based localization systems. The evaluated algorithms are: (i) trilateration using a geometric method, (ii) a closed-form multilateration solution using least squares, (iii) an iterative approach using first-order Taylor series, a recursive solution based on (iv) the Extended Kalman Filter (EKF), and (v) the Unscented Kalman Filter (UKF). In contrast to the existing comparative studies in literature, which are solely based on simulation results, our analysis is based on experimental evaluations. The evaluated algorithms are strictly chosen for a scenario, where a true-range multilateration method is applicable. True-range means the accuracy of the measured ranges is not influenced by the clock drift errors. The performance comparison of the five algorithms is examined and discussed in the paper.

关键词： Kalman filters Covariance matrices Q measurement Navigation Taylor series Standards Noise measurement

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An Analytical Study of Time of Flight Error Estimation in Two-Way Ranging Methods

An Analytical Study of Time of Flight Error Estimation in Tw...

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International Conference on Indoor Positioning and Indoor Navigation (IPIN)

作者： Cung Lian Sang Michael Adams Timm Hörmann Marc Hesse Mario Porrmann Ulrich Rückert Cognitronics and Sensor Systems Group (CITEC) Bielefeld University Bielefeld Germany

In absence of clock synchronization, Two-Way Ranging (TWR) is the most commonly used technique for measuring the distance between two wireless transceivers. The existing time-of-flight (TOF) error estimation model, the IEEE 802.15.4-2011 standard, is specifically based on clock drift error. However, it is insufficient when an in-depth comparative analysis of different TWR methods is required. In this paper, we propose an extended TOF error estimation model for TWR methods, based on the IEEE 802.15.4 standard. Using the proposed model, we perform an analytical study of TOF error estimation among different TWR methods. The model is validated with numerical simulation results. Moreover, we demonstrate the pitfalls of the symmetric double-sided TWR (SDS-TWR) method, which is commonly used to reduce the TOF error due to clock drifts.

关键词： Delays Clocks Distance measurement Error analysis Delay effects Wireless communication Transceivers

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Development of Energy Models for Design Space Exploration of Embedded Many-Core systems

arXiv

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arXiv 2018年

作者： Klarhorst, Christian Flasskamp, Martin Ax, Johannes Jungeblut, Thorsten Kelly, Wayne Porrmann, Mario Rückert, Ulrich Cognitronics and Sensor Systems Group Bielefeld University Citec Bielefeld Germany Science and Engineering Faculty Queensland University of Technology Brisbane Australia

This paper introduces a methodology to develop energy models for the design space exploration of embedded many-core systems. The design process of such systems can benefit from sophisticated models. Software and hardware can be specifically optimized based on comprehensive knowledge about application scenario and hardware behavior. The contribution of our work is an automated framework to estimate the energy consumption at an arbitrary abstraction level without the need to provide further information about the system. We validated our framework with the configurable many-core system CoreVA-MPSoC. Compared to a simulation of the CoreVAMPSoC on gate level in a 28nm FD-SOI standard cell technology, our framework shows an average estimation error of about 4 %. Copyright © 2018, The Authors. All rights reserved.

关键词： Energy utilization

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Detailed estimation of cognitive workload with reference to a modern working environment 9

Detailed estimation of cognitive workload with reference to ...

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Doctoral Consortium - 9th International Joint Conference on Biomedical Engineering systems and Technologies, BIOSTEC 2016

作者： Hörmann, Timm Hesse, Marc Christ, Peter Adams, Michael Menßen, Christian Rückert, Ulrich Cognitronics and Sensor Systems Group CITEC Bielefeld University Universitätsstr. 21-23 Bielefeld33615 Germany

ISBN: (纸本)9783319547169

In modern industry, employees are confronted with ever more complex working tasks. As a consequence, cognitive workload of the employees rises. This makes automatic estimation of cognitive workload a key subject of research. Such an estimate would enable adaptive Human- Machine Interaction that could be used to fit the employees’ workload accordingly to their needs. In this work, a tablet interaction study is presented that is designed to induce cognitive workload. Supervised machine learning methods are used to estimate the induced cognitive workload based on features taken from heart rate, electrodermal activity and user interaction (touch input). Ground truth data is obtained from the subjects’ self-reported cognitive workload. Inter-subject accuracy of the best learner is 74.1% for the detailed 5-class problem and 96.0% for the simplified binary problem. © Springer International Publishing AG 2017.

关键词： Heart

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From CPU to FPGA - Acceleration of Self-Organizing Maps for Data Mining

From CPU to FPGA - Acceleration of Self-Organizing Maps for ...

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International Joint Conference on Neural Networks

作者： Jan Lachmair Thomas Mieth René Griessl Jens Hagemeyer Mario Porrmann Cognitronics and Sensor Systems Group CITEC Bielefeld University

ISBN: (纸本)9781509061839

Big data and machine learning applications are posing steadily increasing challenges to the used compute platforms in terms of performance and energy efficiency. In this paper we utilize the highly scalable heterogeneous server platform RECS for evaluation of a wide variety of hardware platforms ranging from general purpose CPUs via ARM-based SoCs to GPGPUs and FPGAs. The self-organizing map, a popular neural network model for unsupervised clustering and dimensionality reduction, is used as a typical example for machine learning applications in the big data domain. Optimized implementations of the algorithm have been developed for each of the target architectures. An in-depth analysis of the achieved performance and energy efficiency for a wide variety of application parameters shows that no single architecture performs best in terms of energy efficiency for the complete design space. In our study, ARM-based SoCs achieved the highest efficiency for small network sizes while FPGAs and GPGPUs perform best for large data sets. Compared to an implementation based on the Matlab SOM toolbox, our optimized multi-threaded CPU implementation achieves two orders of magnitude higher performance and energy efficiency. Large simulations especially benefit from the FPGA implementation, which outperforms the optimized CPU implementation by a factor of 220 and provides a 28-times higher energy efficiency.

关键词： Machine Learning Big Data Self-Organizing Map SOM GPGPU FPGA FPGA-Cluster ARM-SoC Performance Evaluation self-organising feature maps big data Energy efficiency Field programmable gate arrays central processing units Performance Evaluation GRHL3 gene Artificial Intelligence Machine Learning data mining Neural Networks (Computer)

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Fine-grained prediction of cognitive workload in a modern working environment by utilizing short-term physiological parameters 9

Fine-grained prediction of cognitive workload in a modern wo...

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9th International Conference on Bio-Inspired systems and Signal Processing, BIOSIGNALS 2016 - Part of 9th International Joint Conference on Biomedical Engineering systems and Technologies, BIOSTEC 2016

作者： Hörmann, Timm Hesse, Marc Christ, Peter Adams, Michael Menßen, Christian Rückert, Ulrich Cognitronics and Sensor Systems Group CITEC Bielefeld University Bielefeld Germany

ISBN: (纸本)9789897581700

In this paper we present a method to predict cognitive workload during the interaction with a tablet computer. To set up a predictor that estimates the reflected self-reported cognitive workload we analyzed the information gain of heart rate, electrodermal activity and user input (touch) based features. From the derived optimal feature set we present a Gaussian Process based learner that enables fine-grained and short term detection of cognitive workload. Average inter-subject accuracy in 10-fold cross validation is 74.1 % for the fine-grained 5-class problem and 96.0 % for the binary class problem. Copyright © 2016 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.

关键词： Physiological models

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A connected chair as part of a smart home environment

A connected chair as part of a smart home environment

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International Workshop on Wearable and Implantable Body sensor Networks (BSN)

作者： Marc Hesse André Frank Krause Ludwig Vogel Bhavin Chamadiya Michael Schilling Thomas Schack Thorsten Jungeblut Cognitronics and Sensor Systems Group Cluster of Excellence Cognitive Interaction Technology (CITEC) at Bielefeld University Bielefeld Germany Neurocognition and Action - Biomechanics Group Cluster of Excellence Cognitive Interaction Technology (CITEC) at Bielefeld University Bielefeld Germany Advanced Engineering Group at Hella KGaA Hueck & Co. Lippstadt Germany

ISBN: (纸本)9781509062454

The connected chair is part of the Supportive Personal Coach in the KogniHome project, which offers guided fitness training, relaxation, and assistive functions. The chair comes with integrated sensors, actuators, control logic and wireless transceiver. The sensors are able to measure respiration and heart rate as well as the user's actions. The actuators are used to adjust the chair to the actual user's needs and the transceiver is used to connect wireless sensor nodes and to exchange data with a base station. Additional value is generated by connecting the chair to the smart home environment, which enables and expands novel features and applications.

关键词： Actuators Intelligent sensors Heart rate Radar Training Tracking

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A resource-efficient multi-camera GigE vision IP core for embedded vision processing platforms

A resource-efficient multi-camera GigE vision IP core for em...

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International Conference on ReConFigurable Computing and FPGAs, ReConFig 2015

作者： Ibraheem, Omar W. Irwansyah, Arif Hagemeyer, Jens Porrmann, Mario Rueckert, Ulrich Cognitronics and Sensor Systems Group CITEC Bielefeld University Bielefeld Germany

ISBN: (纸本)9781467394062

In vision processing systems, many applications require multi-camera support. For the connection of the cameras to the processing system, multiple interfaces and a platform capable of handling sustained high data rates are essential. To cope with these requirements, a hardware-based solution using FPGA technology is advisable, especially when targeting space and energy constrained embedded systems. The aim of this work is to develop and implement an FPGA-based scalable and resourceefficient multi-camera GigE Vision IP core for video and image processing. To reduce the number of interfaces needed, the IP core supports the connection of multi-camera interfaces to a single Gigabit Ethernet port using an Ethernet switch. The multicamera GigE Vision IP core is able to extract the raw video data from multiple GigE Vision video streams, reconstruct the video frames from every camera and pass these data for further processing. To test the system, four GigE Vision cameras are used. The IP core is implemented on a Xilinx Virtex-4 FPGA and integrated in a complete video processing platform for a full system realization. In addition to the IP core, bilinear interpolation for image demosaicing with Bayer pattern and an automatic white balance algorithm are implemented for evaluation of the platform. Benchmarking of the hardware implementation has been performed with a total resolution of up to 2048x2048 pixels. Achieved frame rates vary from 25 fps to 345 fps depending on the selected resolution and on the number of used cameras. © 2015 IEEE.

关键词： Field programmable gate arrays (FPGA)

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