this paper presents an error protection method for embedded wavelet codec by combining data hiding with error concealment. For the lowest frequency coefficients, a prolection scheine based data hiding is peifol-ined. ...
详细信息
ISBN:
(纸本)9781424410651
this paper presents an error protection method for embedded wavelet codec by combining data hiding with error concealment. For the lowest frequency coefficients, a prolection scheine based data hiding is peifol-ined. the lowest frequency coefficients, which are taken as the hidden data, are extracted from the compressed bilstream, and embedded back into the same bitstream. the restored hidden data is used to conceal errors. the coefficients that cannot be recovered in other high frequency coefficients reconstruction are predicted through linear interpolation based oil inter-subband correlation. Experimental results show that the proposed method achieves good and stable error performance with minimal additional redundancy.
there are some general procedures to generate the clusterings in clustering ensembles. One can apply different algorithms to create different clusterings of the data. Some clustering algorithms like k-means require in...
详细信息
ISBN:
(纸本)9781424410651
there are some general procedures to generate the clusterings in clustering ensembles. One can apply different algorithms to create different clusterings of the data. Some clustering algorithms like k-means require initialization Of parameters. Different initializations can lead to different clustering results. the parameters of a clustering algorithm, such as the number of clusters, can be altered to create different data clusterings. Different versions of the data can also be used as the input to the clustering algorithm, leading to different partitions. In this paper, we propose a new scheme for constructing multiple independent clusterings using additional artificially generated data. then, we compare our new method with seven general clustering ensemble constructing methods. the experiments show that our approach can achieve higher or comparable performance than the other methods.
data clustering is a long standing research problem in patternrecognition, computer vision, machinelearning, and datamining with applications in a number of diverse disciplines. the goal is to partition a set of n ...
详细信息
In order to obtain more significant information, the increasing hyper-dimensional data is acquired from multi-channel sensors, but the amount of data becomes very large. the quality of the data must be reduced for the...
详细信息
ISBN:
(纸本)9781424410651
In order to obtain more significant information, the increasing hyper-dimensional data is acquired from multi-channel sensors, but the amount of data becomes very large. the quality of the data must be reduced for the data processing and transmission. the central problem is how, to extract the significant features from these data for these purposes. Optimal discrimination plane (ODP) technique based on Fisher's criterion method was developed to reduce the data in the paper. the patterns were projected onto the two orthogonal vectors that built up the ODP, and two-dimensional feature vectors were attained and utilized as features to represent the patterns. Electrocardiogram signals were applied to the analysis as an example in this study A quadratic discriminant function (QDF) based classifier and a threshold vector based classifier were employed to measure the performance of the extracted feature, respectively. the results show the proposed ODP is an effective and feasible technique to extract the features from the hyper-dimensional time series data.
this paper firstly analyses some main similarity measures between vague sets and between elements at present and points out the same disadvantage of these measures. then, some new basic rules are proposed to measure t...
详细信息
ISBN:
(纸本)9781424410651
this paper firstly analyses some main similarity measures between vague sets and between elements at present and points out the same disadvantage of these measures. then, some new basic rules are proposed to measure the rationality of similarity measures. According to the basic rules, a new method of similarity measures is introduced in general situations based on the concept of that the hesitancy/uncertain degree of elements should not be counteracted Some of the necessary conditions of this similarity measure are also pointed out. Finally, the application of the Similarity measure and its effectiveness are illustrated by an example in patternrecognition.
A typical definitional question answering system extracts definition sentences from multiple documents and summarizes the sentences into definitions. In this paper, a new approach is proposed to extract definitional s...
详细信息
ISBN:
(纸本)9781424410651
A typical definitional question answering system extracts definition sentences from multiple documents and summarizes the sentences into definitions. In this paper, a new approach is proposed to extract definitional sentences from web corpus, which is based on soft pattern and ontology. Soft pattern is used to judge whether sentences are definitional with syntactic analysis and ontology can deduce the definitional one with semantic information. the experimental result validates the effectiveness of this method, and the precision reaches 32.7% and is 5.2% higher than the method only based on soft pattern.
Approximate inferring approach of Credal network based on Ant Colony Algorithms is put forward Considering g network inferring of goal-oriented in Bayesian network for the variable decision-maker is interested in live...
详细信息
ISBN:
(纸本)9781424410651
Approximate inferring approach of Credal network based on Ant Colony Algorithms is put forward Considering g network inferring of goal-oriented in Bayesian network for the variable decision-maker is interested in liven some evidence, the paper gives arithmetic for acquiring equivalent Credal network structure of goal-oriented Selecting of these vertexes in Credal network is considered as a multistage decision-making. Based on this, Ant Colony Algorithms is applied for Credal network approximate inferring to reuse the vertexes of high probability of each variable in order to improve of efficiency of inferring arithmetic and avoid some unnecessary computation. Finally, it shows the validity of the approach by simple analysis for a complex Credal network model.
In the field of Multiple Classifiers Combination, diversity among member classifiers is known to be a necessary condition for improving ensemble performance. In this paper we use different types of member classifiers ...
详细信息
ISBN:
(纸本)9781424410651
In the field of Multiple Classifiers Combination, diversity among member classifiers is known to be a necessary condition for improving ensemble performance. In this paper we use different types of member classifiers based on heterogeneous features to increase the diversity when we implement the multiple Classifier System (MCS). Member classifiers adopted in this pap er include the k-NN classifier and the BP network classifier. the combination algorithm is based on Dempster rule of combination. the approaches to generating mass functions corresponding to the types of member classifiers are proposed. It is shown experimentally that the proposed approaches are rational and effective. the approaches proposed in this paper provide a new, way to combine the two different types of classifiers: the k-NN classifiers and the BP network classifiers. thus their corresponding strengths con be fully utilized and their corresponding draw backs can be counteracted.
Based on all phase theory this paper designed three kinds of true 2-D all phase filter bank (true 2-D APFB), which can be used to decompose and recompose image data in true 2-D directly. If quantification error of fil...
详细信息
ISBN:
(纸本)9781424410651
Based on all phase theory this paper designed three kinds of true 2-D all phase filter bank (true 2-D APFB), which can be used to decompose and recompose image data in true 2-D directly. If quantification error of filters is ignored, the true 2-D APFBs have perfect reconstruction property. To reduce computation, they are implemented in lifting scheme. Simulation has shown that true 2-D APFBs have nicer data compression property. Withthe same compression rate, PSNR of IDCT_AFB7.7 is less 0.7dB at most than Daubechies9/7 wavelet's, for true 2-D APFBs adopt quadtree SPIHT coding method which is suitable for separable 2-D wavelet transform. For true 2-D filter banks, binary tree SPIHT coding should be adopted to gel better performance in compression.
Gaussian functions are extensively used in the field of wavelet transform and patternrecognition. In this paper, a fully-progarammable analog circuit for Gaussian function generator using switched-current (SI) techno...
详细信息
ISBN:
(纸本)9781424410651
Gaussian functions are extensively used in the field of wavelet transform and patternrecognition. In this paper, a fully-progarammable analog circuit for Gaussian function generator using switched-current (SI) technology is proposed SI circuits are well suited for this application since the programmability can be implemented and controlled by the clock frequency and the transconductance ratios of SI filters precisely and easily. On the basis of central limit theorem, we synthesize the Gaussian function withthe cascade of several low-pass filters, implemented by SI circuits. theoretical analysis and simulation results show that the proposed method is feasible.
暂无评论