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1.
Many traditional works on off-line Thai handwritten character recognition used a set of local features including circles, concavity, endpoints and lines to recognize hand-printed characters. However, in natural handwriting, these local features are often missing due to rough or quick writing, resulting in dramatic reduction of recognition accuracy. Instead of using such local features, this paper presents a method called multi-directional island-based projection to extract global features from handwritten characters. As the recognition model, two statistical approaches, namely interpolated n-gram model (n-gram) and hidden Markov model (HMM), are proposed. The experimental results indicate that the proposed scheme achieves high accuracy in the recognition of naturally-written Thai characters with numerous variations, compared to some common previous feature extraction techniques. Another experiment with English characters also displays quite promising results.  相似文献   

2.
This paper presents a simple and efficient design method for cosine-modulated filter banks with prescribed stopband attenuation, passband ripple, and channel overlap. The method casts the design problem as a linear minimization of filter coefficients such that their value at ω=π/2M is 0.707, which results in a simpler, more direct design procedure. The weighted constrained least squares technique is exploited for designing the prototype filter for cosine modulation (CM) filter banks. Several design examples are included to show the increased efficiency and flexibility of the proposed method over the exiting methods. An application of the proposed method is considered in the area of sub-band coding of the ECG and speech signals.  相似文献   

3.
In this paper, we consider the H hybrid dynamical output-feedback control problem for discrete-time switched linear systems under asynchronous switching. A time-varying multiple Lyapunov-like-function (MLF) approach is applied to derive sufficient conditions that guarantee the stability and weighted l2-gain performance of the closed-loop systems, where the established conditions explicitly depend on the upper and lower bounds of asynchronous switching delays. An alternative approach is proposed to decouple the bilinear problems of the control synthesis conditions. Convex optimization algorithms are also proposed based on the established conditions to determine the minimum l2-gain performance. Two numerical examples are provided to illustrate the effectiveness of the proposed method, demonstrating significant improvement over the existing results.  相似文献   

4.
李爽 《科技通报》2012,28(8):80-82
针对传统考生身份认证方法的缺陷,提出一种基于人脸识别的考生身份认证系统。首先利用图像采集系统采集考生人脸图像,然后对人脸图像进行特征提取和特征选择,并将人脸特征输入到人脸特征库进行匹配,最后采用支持向量机算法对人脸进行分类识别。实验结果表明,该系统提高了考生身份识别的正确率,减少了识别时间,能够很好满足实际考试的要求。  相似文献   

5.
Multiple-prespecified-dictionary sparse representation (MSR) has shown powerful potential in compressive sensing (CS) image reconstruction, which can exploit more sparse structure and prior knowledge of images for minimization. Due to the popular L1 regularization can only achieve the suboptimal solution of L0 regularization, using the nonconvex regularization can often obtain better results in CS reconstruction. This paper proposes a nonconvex adaptive weighted Lp regularization CS framework via MSR strategy. We first proposed a nonconvex MSR based Lp regularization model, then we propose two algorithms for minimizing the resulting nonconvex Lp optimization problem. According to the fact that the sparsity levels of each regularizers are varying with these prespecified-dictionaries, an adaptive scheme is proposed to weight each regularizer for optimization by exploiting the difference of sparsity levels as prior knowledge. Simulated results show that the proposed nonconvex framework can make a significant improvement in CS reconstruction than convex L1 regularization, and the proposed MSR strategy can also outperforms the traditional nonconvex Lp regularization methodology.  相似文献   

6.
柴继贵 《科技通报》2012,28(8):72-73,76
主要研究了视频图像目标跟踪准确性问题。在基于核的颜色特征统计描述及以此建立视觉目标观测概率方法的基础上,提出了一种改进的粒子滤波视频图像目标跟踪算法。首先,本文给出了基于标准粒子滤波的单特征、单目标跟踪算法,然后针对加权样本参数的选择不同,提出改进思路,最后通过与基于均值移位视觉目标跟踪算法的实验结果对比。提出的改进的粒子滤波跟踪算法在稳健性方面有显著地提高,而且若适当选择视觉跟踪参数,在实时性方面能得到有效地保证。  相似文献   

7.
This paper investigates the problem of robust H fixed-order filtering for a class of linear parameter-varying (LPV) switched delay systems under asynchronous switching that the system parameter matrices and the time delays are dependent on the real-time measured parameters. The so-called asynchronous switching means that there are time delays between the switching of filters and the switching of system modes. By constructing the parameter-dependent and mode-dependent Lyapunov-Krasovskii functional which is allowed to increase during the running time of active subsystem with the mismatched filter, and using the mode-dependent average dwell time (MDADT) switching method, the sufficient conditions for exponential stability and satisfying a novel weighted H criterion are derived. As there exist couplings between Lyapunov-Krasovskii functional matrices and system parameter matrices, we utilize slack matrices to decouple them. Based on the above results, a suitable weighted H fixed-order filter can be obtained in the form of the parameter linear matrix inequalities (PLMIs). By virtue of approximate basis function and gridding technique, the design of weighted H fixed-order filter can be transformed into the solution of the finite dimensional LMIs. Finally, a numerical example is presented to verify both the effectiveness and the low conservatism of the parameter-dependent and mode-dependent fixed-order filtering method proposed in this paper.  相似文献   

8.
Named entity recognition (NER) is mostly formalized as a sequence labeling problem in which segments of named entities are represented by label sequences. Although a considerable effort has been made to investigate sophisticated features that encode textual characteristics of named entities (e.g. PEOPLE, LOCATION, etc.), little attention has been paid to segment representations (SRs) for multi-token named entities (e.g. the IOB2 notation). In this paper, we investigate the effects of different SRs on NER tasks, and propose a feature generation method using multiple SRs. The proposed method allows a model to exploit not only highly discriminative features of complex SRs but also robust features of simple SRs against the data sparseness problem. Since it incorporates different SRs as feature functions of Conditional Random Fields (CRFs), we can use the well-established procedure for training. In addition, the tagging speed of a model integrating multiple SRs can be accelerated equivalent to that of a model using only the most complex SR of the integrated model. Experimental results demonstrate that incorporating multiple SRs into a single model improves the performance and the stability of NER. We also provide the detailed analysis of the results.  相似文献   

9.
This paper investigates the mixed H and passive control problem for a class of nonlinear switched systems based on a hybrid control strategy. To solve this problem, firstly, using the Takagi–Sugeno (T–S) fuzzy model to approximate every nonlinear subsystem, the nonlinear switched systems are modeled as the switched T–S fuzzy systems. Secondly, the hybrid controllers are used to stabilize the switched T–S fuzzy systems. The hybrid controllers consist of dynamic output-feedback controllers for every subsystem and state updating controllers at the switching instant. Thirdly, a new performance index is proposed for switched systems. This new performance index can be viewed as the mixed weighted H and passivity performance. Based on this new performance index, the weighted H control problem and the passive control problem for switched T–S fuzzy systems via the hybrid control strategy are solved in a unified framework. Together the multiple Lyapunov functions (MLFs) approach with the average dwell time (ADT) technique, new design conditions for the hybrid controllers are obtained. Under these conditions, the closed-loop switched T–S fuzzy systems are globally uniformly asymptotically stable with a prescribed mixed H and passivity performance index. Moreover, the desired hybrid controllers can be constructed by solving a set of linear matrix inequalities (LMIs). Finally, the effectiveness of the obtained results is illustrated by a numerical example.  相似文献   

10.
A proposed particle swarm classifier has been integrated with the concept of intelligently controlling the search process of PSO to develop an efficient swarm intelligence based classifier, which is called intelligent particle swarm classifier (IPS-classifier). This classifier is described to find the decision hyperplanes to classify patterns of different classes in the feature space. An intelligent fuzzy controller is designed to improve the performance and efficiency of the proposed classifier by adapting three important parameters of PSO (inertia weight, cognitive parameter and social parameter). Three pattern recognition problems with different feature vector dimensions are used to demonstrate the effectiveness of the introduced classifier: Iris data classification, Wine data classification and radar targets classification from backscattered signals. The experimental results show that the performance of the IPS-classifier is comparable to or better than the k-nearest neighbor (k-NN) and multi-layer perceptron (MLP) classifiers, which are two conventional classifiers.  相似文献   

11.
单一掌纹特征难以全面描述手掌信息,导致识别率较低.为了提高识别率,提出了一种基于Gabor滤波的掌形、掌纹、关节融合手掌识别方法.首先对手掌图像进行预处理,然后提取手掌图像的特征,最后进行特征匹配.实验结果表明,融合多特征的方法是有效的.  相似文献   

12.
This paper is concerned with the distributed H-consensus control problem over the finite horizon for a class of discrete time-varying multi-agent systems with random parameters. First, by utilizing the proposed information matrix, a new formula is established to calculate the weighted covariance matrix of random matrix. Next, by allowing every agent to track the average of the neighbor agents, a novel local H-consensus performance constraint is presented to cater to the local performance analysis. Then, by means of the proposed definition of the stochastic vector dissipativity-like over the finite horizon, a set of sufficient conditions for every agent is obtained such that the controlled outputs of the closed-loop multi-agent systems satisfy the proposed H-consensus performance constraint. As a result, the proposed consensus control algorithm can be executed on each agent in an indeed distributed manner. Finally, a simulation example is employed to verify the effectiveness of the proposed algorithm.  相似文献   

13.
陈杰  马静  李晓峰  郭小宇 《情报科学》2022,40(3):117-125
【目的/意义】本文融合文本和图像的多模态信息进行情感识别,引入图片模态信息进行情感语义增强,旨在 解决单一文本模态信息无法准确判定情感极性的问题。【方法/过程】本文以网民在新浪微博发表的微博数据为实 验对象,提出了一种基于DR-Transformer模型的多模态情感识别算法,使用预训练的DenseNet和RoBERTa模型, 分别提取图片模态和文本模态的情感特征;通过引入Modal Embedding机制,达到标识不同模态特征来源的目的; 采用浅层Transformer Encoder对不同模态的情感特征进行融合,利用Self-Attention机制动态调整各模态信息特征 的权重。【结果/结论】在微博数据集上的实验表明:模型情感识别准确率为 79.84%;相较于基于单一文本、图片模 态的情感分类算法,本模型准确率分别提升了 4.74%、19.05%;相较于对不同模态特征向量进行直接拼接的特征融 合方法,本模型准确率提升了 1.12%。充分说明了本模型在情感识别的问题上具有科学性、合理性、有效性。【创 新/局限】利用 Modal Embedding 和 Self-Attention 机制能够有效的融合多模态信息。微博网络舆情数据集还需进 一步扩充。  相似文献   

14.
In this paper, switched circuits are modeled based on wavelet decomposition and neural network. Also describes the usage of wavelet decomposition and neural network for modeling and simulation of nonlinear systems. The switched circuits are piecewise-linear circuits. At each position of switch the circuit is linear but when considered all switching positions of the circuit it becomes nonlinear. An important problem which arises in modeling switched circuit is high structural complexity. In this study, wavelet decomposition is used for feature extracting from input signals and neural network is used as an intelligent modeling tool. Two performance measures root-mean-square (RMS) and the coefficient of multiple determinations (R2) are given to compare the predicted and computed values for model validation. The evaluated R2 value is 0.9985 and RMS value is 0.0099. All simulations showed that the proposed method is more effective and can be used for analyzing and modeling switched circuits. When we consider obtained performance, we can easily say that the proposed method can be used efficiently for modeling any other nonlinear dynamical systems.  相似文献   

15.
One of the important image processing tasks is to effectively reduce a noise from a digital image while keeping its features intact. In this paper, a new noise removal method for color images corrupted by the mixture of the impulsive and Gaussian noises is proposed. In the proposed method, firstly, a tentative output image, in which the noise is removed almost perfectly, is obtained by using the iterative robust switching vector median-based vector ε-filter, which is realized by hybridizing the robust switching vector median filter and the vector ε-filter and is newly proposed here. Then the residual components between the input and the tentative output images are calculated, and image components constituting edges, corner and other image details are extracted from the residual components by using the correlation characteristic in RGB components. Consequently, a final output is obtained by adding the extracted image components into the tentative output image. The effectiveness and the validity of the proposed method are verified by some experiments using the natural color images.  相似文献   

16.
儒林 《科技通报》2012,28(4):94-96
当前主流的人脸识别算法,都是把原有的彩色图像转化为灰度图后,采用基于灰度图像的特征抽取与识别算法进行分类识别。人们在实际操作过程中,只是使用一组简单的加权系数实现从彩色图像到灰度图的转换,这并不能很好的体现R,G,B 3个颜色分量之间的次重关系。本文根据人脸图像颜色组成的特点,对彩色人脸图像的R,G,B 3个分量的颜色信息进行特征抽取与分析,从中找出鉴别特征的三基色系数表示方法,把彩色图像转化为灰度图。最后,在国际通用的AR标准彩色人脸库中进行了大量实验,验证了本文算法的有效性。  相似文献   

17.
Starck等人的图像增强方法不能有效增强SAR图像中的边缘特征.为此,提出一种curvelet域SAR图像特征增强新方法.该方法充分利用curvelet变换多尺度多方向特性及其良好的各向异性特点,在curvelet域内提取图像的边缘特征,并定位特征curvelet系数.通过增强特征curvelet系数,达到增强图像边缘特征的目的.实验结果表明,与Starck等人的方法相比,本文算法能够更加有效性地增强SAR图像的边缘特征.  相似文献   

18.
This paper is concerned with the event-based weighted residual generator design via non-parallel distribution compensation (PDC) scheme for fault diagnosis in discrete-time T–S fuzzy systems, under consideration of the imperfect premise matching membership functions. An event-triggered mechanism is firstly introduced to save communication resources, which leads to the premise variables of the system and observer to be asynchronous. Then, a fuzzy diagnostic observer with mismatched premise variables is designed to estimate the unmeasurable states of the system. Moreover, by using non-PDC method, a diagnostic observer-based weighted residual generator is established to improve the fault detection (FD) performance by using the information provided by each local system, in which the membership functions structure of the diagnostic observer and residual generator need not to be the same as the systems, and the L/L2 and L FD scheme is used to optimize the FD performance. Finally, two simulation results are provided to show the efficiency of the proposed non-PDC method.  相似文献   

19.
Breast cancer is one of the leading causes of death among women worldwide. Accurate and early detection of breast cancer can ensure long-term surviving for the patients. However, traditional classification algorithms usually aim only to maximize the classification accuracy, failing to take into consideration the misclassification costs between different categories. Furthermore, the costs associated with missing a cancer case (false negative) are clearly much higher than those of mislabeling a benign one (false positive). To overcome this drawback and further improving the classification accuracy of the breast cancer diagnosis, in this work, a novel breast cancer intelligent diagnosis approach has been proposed, which employed information gain directed simulated annealing genetic algorithm wrapper (IGSAGAW) for feature selection, in this process, we performs the ranking of features according to IG algorithm, and extracting the top m optimal feature utilized the cost sensitive support vector machine (CSSVM) learning algorithm. Our proposed feature selection approach which can not only help to reduce the complexity of SAGASW algorithm and effectively extracting the optimal feature subset to a certain extent, but it can also obtain the maximum classification accuracy and minimum misclassification cost. The efficacy of our proposed approach is tested on Wisconsin Original Breast Cancer (WBC) and Wisconsin Diagnostic Breast Cancer (WDBC) breast cancer data sets, and the results demonstrate that our proposed hybrid algorithm outperforms other comparison methods. The main objective of this study was to apply our research in real clinical diagnostic system and thereby assist clinical physicians in making correct and effective decisions in the future. Moreover our proposed method could also be applied to other illness diagnosis.  相似文献   

20.
Many machine learning algorithms have been applied to text classification tasks. In the machine learning paradigm, a general inductive process automatically builds a text classifier by learning, generally known as supervised learning. However, the supervised learning approaches have some problems. The most notable problem is that they require a large number of labeled training documents for accurate learning. While unlabeled documents are easily collected and plentiful, labeled documents are difficultly generated because a labeling task must be done by human developers. In this paper, we propose a new text classification method based on unsupervised or semi-supervised learning. The proposed method launches text classification tasks with only unlabeled documents and the title word of each category for learning, and then it automatically learns text classifier by using bootstrapping and feature projection techniques. The results of experiments showed that the proposed method achieved reasonably useful performance compared to a supervised method. If the proposed method is used in a text classification task, building text classification systems will become significantly faster and less expensive.  相似文献   

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