Papers by Author: Xiao Yan Chen

Abstract: Sparse decompression is a new theory for signal processing, having the advantage in that the base (dictionary) used in this theory is over-complete, and can reflect the nature of signa1. So the sparse decompression of signal can get sparse representation, which is very important in data compression. In this paper, a novel ECG compression method for multi-channel ECG signals was introduced based on the Simultaneous Orthogonal Matching Pursuit (S-OMP). The proposed method decomposes multi-channel ECG signals simultaneously into different linear expansions of the same atoms that are selected from a redundant dictionary, which is constructed by Hermite fuctions and Gobar functions in order to the best match the characteristic of the ECG waveform. Compression performance has been tested using a subset of multi-channel ECG records from the St.-Petersburg Institute of Cardiological Technics database, the results demonstrate that much less atoms are selected to present signals and the compression ratio of Multi-channel ECG can achieve better performance in comparison to Simultaneous Matching Pursuit (SMP).

Abstract: The burning point of coal sample is a crucial physical property of coal, and it is also a key technical parameter for the exploitation, transportation, and application of coal. The national standard for coal sample burning point detection prescribes a strict rising rate of temperature when coal samples being heated. To meet with this engineering requirement, we introduce a scheme of a coal sample burning point detecting instrument, which is based on an AT89C55 MCU. The characteristics, key techniques, and solutions of the temperature control system are introduced with respect to the instrument. We employ a self-tunning Dahlin controller with a Recursive Least Squares with Exponential Forgetting (RLSEF) algorithm to solve the control problems of this time-delay, big inertia, and time-variable plant (coal sample heating furnace). Simulations show that the self-tunning Dahlin controller is able to not only compensate the time-delay and big inertia of the plant and but also adapt to the variations of plant parameters, so that the requirement for the rising rate of temperature can be fulfilled effectively.