A digital filtering method is presented to compensate the dynamic characteristics of measuring systems.The compensation filter has an infinite impulse response property and is designed by system identification approac...A digital filtering method is presented to compensate the dynamic characteristics of measuring systems.The compensation filter has an infinite impulse response property and is designed by system identification approach from the known input output pairs of the measuring system.Applications of this method to eliminating the distortions of measured waveform in transient pulse measurement are investigated.Experimental results show that the measurement errors caused by the sensor are reduced to be very small after the use of the compensation filter.展开更多
In this paper we revise the moment theory for pattern recognition designed, to extract patterns from the noisy character datas, and develop unconstrained handwritten. Amazigh character recognition method based upon or...In this paper we revise the moment theory for pattern recognition designed, to extract patterns from the noisy character datas, and develop unconstrained handwritten. Amazigh character recognition method based upon orthogonal moments and neural networks classifier. We argue that, given the natural flexibility of neural network models and the extent of parallel processing that they allow, our algorithm is a step forward in character recognition. More importantly, following the approach proposed, we apply our system to two different databases, to examine the ability to recognize patterns under noise. We discover overwhelming support for different style of writing. Moreover, this basic conclusion appears to remain valid across different levels of smoothing and insensitive to the nuances of character patterns. Experiments tested the effect of set size on recognition accuracy which can reach 97.46%. The novelty of the proposed method is independence of size, slant, orientation, and translation. The performance of the proposed method is experimentally evaluated and the promising results and findings are presented. Our method is compared to K-NN （k-nearest neighbors） classifier algorithm; results show performances of our method.展开更多
文摘A digital filtering method is presented to compensate the dynamic characteristics of measuring systems.The compensation filter has an infinite impulse response property and is designed by system identification approach from the known input output pairs of the measuring system.Applications of this method to eliminating the distortions of measured waveform in transient pulse measurement are investigated.Experimental results show that the measurement errors caused by the sensor are reduced to be very small after the use of the compensation filter.
文摘In this paper we revise the moment theory for pattern recognition designed, to extract patterns from the noisy character datas, and develop unconstrained handwritten. Amazigh character recognition method based upon orthogonal moments and neural networks classifier. We argue that, given the natural flexibility of neural network models and the extent of parallel processing that they allow, our algorithm is a step forward in character recognition. More importantly, following the approach proposed, we apply our system to two different databases, to examine the ability to recognize patterns under noise. We discover overwhelming support for different style of writing. Moreover, this basic conclusion appears to remain valid across different levels of smoothing and insensitive to the nuances of character patterns. Experiments tested the effect of set size on recognition accuracy which can reach 97.46%. The novelty of the proposed method is independence of size, slant, orientation, and translation. The performance of the proposed method is experimentally evaluated and the promising results and findings are presented. Our method is compared to K-NN （k-nearest neighbors） classifier algorithm; results show performances of our method.
