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Sludge volume index (SVI) can evaluate and reflect the aggregation of activated sludge sediment properties accurately. It is an important parameter to predict sludge bulking. Generally, if SVI value is too high, the description is sludge settling performance is poor. It will occur or has occurred sludge bulking. But SVI cannot be online measurement, offline assay data obtained for a long time or other...
Transcranial magnetic simulations (TMS) is an effective tool for studying pathophysiology of dystonia as well as various other movement or cognitive functions of the brain. To study how TMS induces complex neuronal responses and plasticity, we built computational models for primary motor cortex, basal ganglia and synaptic plasticity. Our models have successfully reproduced neuronal responses to TMS,...
Artificial immune system [1] is computational system inspired by the principles and processes of the vertebrate immune system. It has been applied gradually in many fields upon powerful abilities of information processing and problem solution [2–3]. In this paper, handwritten Russian uppercase character recognition strategy using artificial immune system was proposed and carefully experimented. With...
In this paper, a novel reversible watermarking method based on the coefficient adjustment technique is proposed. A host image is first decomposed into the integer wavelet transform (IWT) domain. Subsequently, a secret message is embedded into the low-high (LH), high-low (HL), and high-high (HH) sub-bands of the IWT using the coefficient adjustment method. Experiments confirm that the proposed method...
The natural gradient algorithm is the most basic independent component analysis (ICA) algorithm. Because the traditional natural gradient algorithm adopts fixed-step-size, the choice of step size directly affects the convergence speed and steady-state performance. This paper proposes an improved natural gradient algorithm by using the difference between the separation matrixes to control the factor...
AdaBoost has been the representation of ensemble learning algorithm because of its excellent performance. However, due to its longtime training, AdaBoost was complained about by people and this defect limits the practical application. Bagging is a rapid method of training and supports for parallel computing. One of important factors that can affect the performance of ensemble learning is the diversity...
The fuzzy logic was applied into the neural network and the application of fault diagnosis for boiler system with the integrated fuzzy neural network is investigated on the basis of the introductions of the basic principle of artificial neural network (ANN) and the principle of fault diagnosis for boiler system based on neural network. A example of training process and testing results about the sample...
In this paper, we first propose a method to transform from LDA to PCA with the discriminative information embedded in a whitening transformation, and then we propose a simple support vector machine formulation to LDA. The results of experiments of face recognition conducted on ORL database show the effectiveness of the proposed method.
Traditional planar shape representations cannot efficiently solve some problems such as recognition under occlusion, reconstruction and partial matching. In this paper, an improved shape representation by the extraction of contour curvature is presented based on the invariance of curvature. Then the invariance and discrete approximation solution are demonstrated. Finally the reconstruction method...
This paper introduces a new concept of designing a discriminant analysis method (discriminator), which starts from a local mean based nearest neighbor (LM-NN) classifier and uses its decision rule to direct the design of a discriminator. The derived discriminator, called local mean based nearest neighbor discriminator (LM-NND), matches the LM-NN classifier optimally in theory. The proposed LM-NND...
The basic sampling importance resampling algorithm is the basic for improving particle filter methods which are widely utilized in optimal filtering problems. In our paper, we introduce a modified basic SIR algorithm and analyze the convergence property of the modified basic SIR algorithm. Furthermore, when the recursive time is finite and the forth-order moment of the interesting function w.r.t the...
This paper introduces the minimal local reconstruction error (MLRE) as a similarity measure and presents a MLRE-based classier. From the geometric meaning of the minimal local reconstruction error, we derive that the MLRE-based classifier is a generalization of the conventional nearest neighbor classier and the nearest neighbor line and plane classifiers. We further apply the MLRE measure to characterize...
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