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We developed a front-end ASIC amplifier of time projection chamber for an experiment to measure neutron lifetime. The precise determination of neutron lifetime is very important to understand the early universe in Big bang nucleosynthesis. The heat generation of frond-end amplifier may become the potential systematic uncertainty in determining the lifetime. In order to overcome this deficit, we have...
In this paper, we propose an effective image compression noise reduction system based on the total variation (TV) regularization method. Our system allows the removal of MPEG-2 compression noise such as mosquito noise and blocky noise without losing picture sharpness. This method is particularly useful for HDTV terrestrial broadcasting with insufficient transmission bandwidth for noise-free HDTV pictures...
This paper presents the results from a neural network rule extraction algorithm applied to the LED display recognition problem. We show that pruned neural networks with small number of hidden nodes and connections are able to recognize all the 10 digits from 0 to 9. Earlier work by other researchers demonstrated how symbolic fuzzy rules can be extracted from trained neural networks to solve this problem...
The sigma-delta cellular neural network (SD-CNN) is a novel framework of spatial domain sigma-delta modulation utilizing neuro dynamics. Also, it has signal reconstruction and noise shaping characteristics that are important sigma-delta properties. Although the noise shaping effect with the oversampling technique plays very important role for drastic quantization noise reduction in binary digital...
The spurious minima in optimizing operation is one of the difficulty for Lyapunov function. In this paper, novel lossless image coding method based on lifting scheme using discrete-time cellular neural networks (DT-CNNs) with annealing approach is proposed. In the proposed, the image prediction of lifting scheme is implemented by DT-CNNs solving the nonlinear optimization problem of Lyapunov energy...
The sigma-delta cellular neural network (SD-CNN) is a complete framework of a spatial domain sigma-delta modulator, and has a very high image reconstruction (AD-to-DA) performance. In this architecture, the A-template, given by a 2D low pass filter (LPF), is used for a digital to analogue converter (DAC), the C-template works as an integrator, and the nonlinear output function is for the bilevel output...
In this paper, we consider determination of separating hyperplane where some data points are treated as noise. Pocket algorithm with ratchet is an algorithm for this kind of problems, but it does not guarantee minimal number of noisy instances. By noticing that a hyperplane can be determined by selecting n points among data (where n is the dimension of the data), we can guarantee that point. Actually,...
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