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A constructive method for the design of nonlinear observers is discussed. To formulate conditions for the construction of the observer gains, stability results for nonlinear singularly perturbed systems are utilised. The nonlinear observer is designed directly in the given coordinates, where the error dynamics between the plant and the observer becomes singularly perturbed by a high-gain part of the observer injection, and the information of the slow manifold is exploited to construct the observer gains of the reduced-order dynamics. This is in contrast to typical high-gain observer approaches, where the observer gains are chosen such that the nonlinearities are dominated by a linear system. It will be demonstrated that the considered approach is particularly suited for self-sensing electromechanical systems. Two variants of the proposed observer design are illustrated for a nonlinear electromagnetic actuator, where the mechanical quantities, i.e. the position and the velocity, are not measured
Objective: This paper presents an algorithm for non-invasive sleep stage identification using respiratory, heart rate and movement signals. The algorithm is part of a system suitable for long-term monitoring in a home environment, which should support experts analysing sleep. Approach: As there is a strong correlation between bio-vital signals and sleep stages, multinomial logistic regression was chosen for categorical distribution of sleep stages. Several derived parameters of three signals (respiratory, heart rate and movement) are input for the proposed method. Sleep recordings of five subjects were used for the training of a machine learning model and 30 overnight recordings collected from 30 individuals with about 27 000 epochs of 30 s intervals each were evaluated. Main results: The achieved rate of accuracy is 72% for Wake, NREM, REM (with Cohen's kappa value 0.67) and 58% for Wake, Light (N1 and N2), Deep (N3) and REM stages (Cohen's kappa is 0.50). Our approach has confirmed the potential of this method and disclosed several ways for its improvement. Significance: The results indicate that respiratory, heart rate and movement signals can be used for sleep studies with a reasonable level of accuracy. These inputs can be obtained in a non-invasive way applying it in a home environment. The proposed system introduces a convenient approach for a long-term monitoring system which could support sleep laboratories. The algorithm which was developed allows for an easy adjustment of input parameters that depend on available signals and for this reason could also be used with various hardware systems.
The business model canvas (BMC) and the lean start-up manifesto (LSM) have been changing both the entrepreneurial education and, on the practical side, the mindset in setting up innovative ventures since the burst of the dot-com bubble. However, few empirical insights on the business model implementation patterns that distinguish between digital and non-digital innovative ventures exist. Connecting practical management tools to network theory as well as to the theory of organizational learning, this paper investigates evolution patterns of digital and non-digital business models out of the deal flow of an innovation intermediary. For this purpose, a multi-dimensional quantitative content analysis research design is applied to 242 ventures' business plans. The measured strength of transaction relations to customers, suppliers, people, and financiers has been combined with performance indicators of the sampled ventures. The results indicate that in order to succeed, digital ventures iterate their business on the market early and search for investment afterwards. Contrariwise, non-digital ventures already need financial investments in the early stages to set up a product ready to be tested on the market. In both groups we found strong evidence that specific evolutionary patterns relate to higher rates of success.
Error correction coding based on soft-input decoding can significantly improve the reliability of non-volatile flash memories. This work proposes a soft-input decoder for generalized concatenated (GC) codes. GC codes are well suited for error correction in flash memories for high reliability data storage. We propose GC codes constructed from inner extended binary Bose-Chaudhuri-Hocquenghem (BCH) codes and outer Reed-Solomon codes. The extended BCH codes enable an efficient hard-input decoding. Furthermore, a low-complexity soft-input decoding method is proposed. This bit-flipping decoder uses a fixed number of test patterns and an algebraic decoder for soft-decoding. An acceptance criterion for the final candidate codeword is proposed. Combined with error and erasure decoding of the outer Reed-Solomon codes, this acceptance criterion can improve the decoding performance and reduce the decoding complexity. The presented simulation results show that the proposed bit-flipping decoder in combination with outer error and erasure decoding can outperform maximum likelihood decoding of the inner codes.
The Burrows–Wheeler transformation (BWT) is a reversible block sorting transform that is an integral part of many data compression algorithms. This work proposes a memory-efficient pipelined decoder for the BWT. In particular, the authors consider the limited context order BWT that has low memory requirements and enable fast encoding. However, the decoding of the limited context order BWT is typically much slower than the encoding. The proposed decoder pipeline provides a fast inverse BWT by splitting the decoding into several processing stages which are executed in parallel.
The introduction of multiple-level cell (MLC) and triple-level cell (TLC) technologies reduced the reliability of flash memories significantly compared with single-level cell flash. With MLC and TLC flash cells, the error probability varies for the different states. Hence, asymmetric models are required to characterize the flash channel, e.g., the binary asymmetric channel (BAC). This contribution presents a combined channel and source coding approach improving the reliability of MLC and TLC flash memories. With flash memories data compression has to be performed on block level considering short-data blocks. We present a coding scheme suitable for blocks of 1 kB of data. The objective of the data compression algorithm is to reduce the amount of user data such that the redundancy of the error correction coding can be increased in order to improve the reliability of the data storage system. Moreover, data compression can be utilized to exploit the asymmetry of the channel to reduce the error probability. With redundant data, the proposed combined coding scheme results in a significant improvement of the program/erase cycling endurance and the data retention time of flash memories.
Generalised concatenated (GC) codes are well suited for error correction in flash memories for high-reliability data storage. The GC codes are constructed from inner extended binary Bose–Chaudhuri–Hocquenghem (BCH) codes and outer Reed–Solomon codes. The extended BCH codes enable high-rate GC codes and low-complexity soft input decoding. This work proposes a decoder architecture for high-rate GC codes. For such codes, outer error and erasure decoding are mandatory. A pipelined decoder architecture is proposed that achieves a high data throughput with hard input decoding. In addition, a low-complexity soft input decoder is proposed. This soft decoding approach combines a bit-flipping strategy with algebraic decoding. The decoder components for the hard input decoding can be utilised which reduces the overhead for the soft input decoding. Nevertheless, the soft input decoding achieves a significant coding gain compared with hard input decoding.
This work studies a wind noise reduction approach for communication applications in a car environment. An endfire array consisting of two microphones is considered as a substitute for an ordinary cardioid microphone capsule of the same size. Using the decomposition of the multichannel Wiener filter (MWF), a suitable beamformer and a single-channel post filter are derived. Due to the known array geometry and the location of the speech source, assumptions about the signal properties can be made to simplify the MWF beamformer and to estimate the speech and noise power spectral densities required for the post filter. Even for closely spaced microphones, the different signal properties at the microphones can be exploited to achieve a significant reduction of wind noise. The proposed beamformer approach results in an improved speech signal regarding the signal-to-noise-ratio and keeps the linear speech distortion low. The derived post filter shows equal performance compared to known approaches but reduces the effort for noise estimation.
Im vorliegenden Aufsatz wird das grundlegende Vorgehen zur Berechnung der Durchbiegung im gerissenen Zustand inklusive Berücksichtigung von Kriechen und Schwinden vorgestellt. Dabei werden aufbauend auf den Vorgaben des EC2 verschiedene Verfahren mit unterschiedlichen Genauigkeitsniveaus für Balken und einachsig gespannte Platten erläutert. Für einfache Systeme können diese Verfahren auch von Hand durchgeführt werden und bieten dabei ein hohes Maß an Kontrolle über den Rechenablauf. Anschließend wird die Ermittlung der Schwindverformungen genauer betrachtet, welche nur mit hohem Rechenaufwand durchgeführt werden kann. Für eine Auswahl von Systemen können Diagramme mit Multiplikationsfaktoren hergeleitet werden, welche die Berechnung stark vereinfachen. Des Weiteren wird auf die Verformungsberechnung im Zustand II für Plattentragwerke eingegangen. Dabei werden sowohl die Berechnung mit FE‐Plattenprogrammen, welche oftmals entsprechende Funktionen anbieten, als auch vereinfachte manuelle Verfahren vorgestellt. Die Grundlagen der Rissbildung lassen sich von Stabtragwerken auf Platten übertragen, allerdings entstehen dabei neue Fragestellungen, wie beispielsweise zum Vorgehen bei der Steifigkeitsabminderung oder zum Einfluss der Schnittgrößenumlagerung infolge Rissbildung. In diesem Bereich besteht daher noch Forschungsbedarf.