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This work investigates data compression algorithms for applications in non-volatile flash memories. The main goal of the data compression is to minimize the amount of user data such that the redundancy of the error correction coding can be increased and the reliability of the error correction can be improved. A compression algorithm is proposed that combines a modified move-to-front algorithm with Huffman coding. The proposed data compression algorithm has low complexity, but provides a compression gain comparable to the Lempel-Ziv-Welch algorithm.
In this paper, a gain-scheduled nonlinear control structure is proposed for a surface vessel, which takes advantage of extended linearisation techniques. Thereby, an accurate tracking of desired trajectories can be guaranteed that contributes to a safe and reliable water transport. The PI state feedback control is extended by a feedforward control based on an inverse system model. To achieve an accurate trajectory tracking, however, an observer-based disturbance compensation is necessary: external disturbances by cross currents or wind forces in lateral direction and wave-induced measurement disturbances are estimated by a nonlinear observer and used for a compensation. The efficiency and the achieved tracking performance are shown by simulation results using a validated model of the ship Korona at the HTWG Konstanz, Germany. Here, both tracking behaviour and rejection of disturbance forces in lateral direction are considered.
The method of signal injection is investigated for position estimation of proportional solenoid valves. A simple observer is proposed to estimate a position-dependent parameter, i.e. the eddy current resistance, from which the position is calculated analytically. Therefore, the relationship of position and impedance in the case of sinusoidal excitation is accurately described by consideration of classical electrodynamics. The observer approach is compared with a standard identification method, and evaluated by practical experiments on an off-the-shelf proportional solenoid valve.
Several possibilities of tests under load on a chassis dynamometer are presented. Consumption measurements according standard driving cycles as the New European Drive Cycle (NEDC) and Worldwide harmonized light duty test procedure/cycle (WLTP/WLTC) make special attention to the observance of the regulations necessary. The rotational masses of inertia and the load depending on velocity have to match the required values. Load tests as well allow the determination of the maximum acceleration in the current gear and the slippage of the driven wheels.
The aim of the paper is to present the simulation of the sweeping process based on a mathematical model that includes the drag force, the lift force, the sideway force, and the gravity. At the beginning, it is presented a short history of the street sweepers, some considerations about the sweeping process and the parameters of the sweeping process. Considering the developed model, in Matlab there is done some simulation for the trajectory of a spherical pebble. The obtained results are presented in graphical shape.
Increasing robustness of handwriting recognition using character N-Gram decoding on large lexica
(2016)
Offline handwriting recognition systems often include a decoding step, that is retrieving the most likely character sequence from the underlying machine learning algorithm. Decoding is sensitive to ranges of weakly predicted characters, caused e.g. by obstructions in the scanned document. We present a new algorithm for robust decoding of handwriting recognizer outputs using character n-grams. Multidimensional hierarchical subsampling artificial neural networks with Long-Short-Term-Memory cells have been successfully applied to offline handwriting recognition. Output activations from such networks, trained with Connectionist Temporal Classification, can be decoded with several different algorithms in order to retrieve the most likely literal string that it represents. We present a new algorithm for decoding the network output while restricting the possible strings to a large lexicon. The index used for this work is an n-gram index with tri-grams used for experimental comparisons. N-grams are extracted from the network output using a backtracking algorithm and each n-gram assigned a mean probability. The decoding result is obtained by intersecting the n-gram hit lists while calculating the total probability for each matched lexicon entry. We conclude with an experimental comparison of different decoding algorithms on a large lexicon.
The magneto-mechanical behavior of magnetic shape memory (MSM) materials has been investigated by means of different simulation and modeling approaches by several research groups. The target of this paper is to simulate actuators driven by MSM alloys and to understand the MSM element behavior during actuation, which shall lead to an increased performance of the actuator. It is shown that internal and external stresses should be taken into consideration using numerical computation tools for magnetic fields in an efficient way.