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Advances in intelligent systems and computing 2014年 215卷 363-373页

作者： Zhang, Hao Liang, Jianyi Liu, Ye Wang, Hang Zhang, Liqing MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China

Motor imagery-based BCI-FES rehabilitation system has been proved to be effective in the treatment of movement function recovery. Common Spatial Pattern (CSP) and Support Vector Machine (SVM) are commonly used in the feature extraction and classification of Two-classes motor imagery. However, motor imagery signals of stroke patients are irregular due to the damage of the specified brain area. Traditional CSP is not able to detect the optimal projection direction on such EEG data recorded from stroke patients under the interference of irregular patterns. In this paper, an adaptive CSP method is proposed to deal with these unknown irregular patterns. In the method, two models are trained and updated by using different subsets of the original data in every iteration procedure. The method is applied on the EEG datasets of several stroke subjects comparing with traditional CSP-SVM. The results also provide an evidence of the feasibility of our BCI-FES rehabilitation system. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Support vector machines

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New words identification based on ensemble methods

New words identification based on ensemble methods

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2nd International Conference on Precision Mechanical Instruments and Measurement Technology, ICPMIMT 2014

作者： Zhang, Chen Chen, Yu-Quan Department of Computer Science and Engineer Shanghai Jiao Tong University Shanghai China MOE-Microsoft Key Lab. for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9783038351948

In order to identify new words in huge Chinese corpus efficiently, this paper comes up with an algorithm based on ensemble methods. At first we perform Chinese word segmenting with Trie and build segment-tree. Then we select words pattern drawing method, frequency filtering, independent word probability and naive Bayes model to be sub-models of ensemble methods and train them independently. At last we integrate results from different sub-models with a multi-layer model. In experiment, this algorithm is proved to be quite fast as well as product precise and high-coverage results. © (2014) Trans Tech Publications, Switzerland.

关键词： Bayesian networks

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ECG Representation with Simulated 2D and 3D VCG using Prior Knowledge Based Weighted PCA

ECG Representation with Simulated 2D and 3D VCG using Prior ...

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2012 International Conference on Medical Physics and Biomedical Engineering(ICMPBE 2012)

作者： Kai Huang Liqing Zhang MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and EngineeringShanghai Jiao Tong University

It is important to use prior knowledge of signal characteristics and their distribution in time-frequency space to extract valuable information from noisy medical ***,the noise in an ECG often has a wide bandwidth which is difficult for approaches based on filters or *** adaptive filters such as Wigner filters or Kalman filters are able to remove wide-bandwidth noise,signal waveform distortion may be brought *** we propose a new noise reduction method which uses the inherent information redundancy in an *** construct 2D and 3D Vectorcardiographs from a standard 12 channel ECG signal,and then project them onto the channel axes to recreate the ECG ***,we take advantage of prior knowledge of where the valuable information is in the *** then apply a knowledge-based weighted Principle Component Analysis to reduce the noise and extract the valuable waveform with the recreated ECG signal.

关键词： Prior Knowledge based Weighted PCA,ECG denoise,information redundancy

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SECOND ORDER VECTOR TAYLOR SERIES BASED ROBUST SPEECH RECOGNITION

SECOND ORDER VECTOR TAYLOR SERIES BASED ROBUST SPEECH RECOGN...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Suliang Bu Yanmin Qian Khe Chai Sim Yongbin You Kai Yu MOE-Microsoft Key Lab. for Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Department of Computer Science National University of Singapore

ISBN: (纸本)9781479928941

Vector Taylor Series (VTS) model based compensation approach has been successfully applied to various robust speech recognition tasks. In this paper, a novel method to derive the formula to calculate the static and dynamic statistics based on second-order VTS (sVTS) is presented, which provides a new insight on the VTS approximation. Lengthy derivation could therefore be avoided when high order VTS is used and the proposed approach is more compact and easier to implement compared to previous high order VTS approaches. Experiments on Aurora 4 showed that the proposed sVTS based model compensation approach obtained 16.7% relative WER reduction over traditional first-order VTS (fVTS) approach.

关键词： Speech recognition Vessel traffic services VTS formula

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How faithfully can π be interpreted in SA?

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Science China(Information Sciences) 2013年第3期56卷 82-96页

作者： LONG Huan FU YuXi Basic Studies in Computing Science Department of Computer ScienceMOE-MS Key Laboratory for Intelligent Computing and Intelligent SystemsShanghai Jiao Tong University

The π calculus and the safe ambient calculus are two of the widely studied variants of process calculi in the field of concurrency *** former is the most classic model for mobile processes and the latter is well known for its nested ***,the relationship between these two models deserves further *** this paper,we reinvestigate this problem *** first give the strengthened encoding *** we propose the encoding of the synchronous π-calculus into the safe ambients *** encoding scheme is a generalization and improvement of Levi and Sangiorgi’s work when moving from the asynchronous π-calculus to the synchronous π-*** show the merits of the encoding by checking the mentioned criteria.

关键词： encoding expressiveness synchronous π-calculus safe ambients

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An interpretation of Erlang into value-passing calculus

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Journal of Networks 2013年第7期8卷 1504-1513页

作者： Huang, Hao Yang, Fei Department of Computer Science Shanghai Jiaotong University MOE-MS Key Laboratory for Intelligent Computing and Intelligent Systems China

In this paper we present a new process calculus VPCΣ and an interpretation for core Erlang. VPCΣ is at least as expressive as VPC and it is more effective for verification with some built-in functions. The wellestablished symbolic bisimulation in value-passing calculus is now helpful for solving the infinite-state space problem of data values in equivalence checking and verfication. Compared to the previous formalization work of modeling core Erlang in π-calculus, the new interpretation has the following main merits: some essential features for Erlang are implemented faithfully;and above all the soundness of the interpretation is proved with respect to late symbolic bisimulation. © 2013 ACADEMY PUBLISHER.

关键词： Calculations

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Process Passing Calculus,Revisited

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Journal of Shanghai Jiaotong university(Science) 2013年第1期18卷 29-36页

作者：尹强龙环 Laboratory of Basic Study in Computing Science MOE-MS Key Laboratory for Intelligent Computing and Intelligent SystemsDepartment of Computer Science and EngineeringShanghai Jiaotong University

In the context of process calculi, higher order π calculus （A calculus） is prominent and popular due to its ability to transfer processes. Motivated by the attempt to study the process theory in an integrated way, we give a system study of A calculus with respect to the model independent framework. We show the coincidence of the context bisimulation to the absolute equality. We also build a subbisimilarity relation from A calculus to the π calculus.

关键词： higher order π-calculus encoding expressiveness bisimulation

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Motion deblurring using super-sparsity

Motion deblurring using super-sparsity

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20th International Conference on Neural Information Processing, ICONIP 2013

作者： Zhao, Jingxiong Zhao, Haohua Zhang, Keting Zhang, Liqing MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai Jiao Tong University China

ISBN: (纸本)9783642420504

Motion blur is caused by the camera shake during the exposure in which the blur kernel describes the trace of shaking. Based on this generating process of the kernel , we observed that the distribution of the kernel obeys super-sparsity, as the natural images. Recent works mostly exploit various kinds of priors in their models, but focus on the the speed or a close-form formulation for convenience of mathematical calculation ignoring the intrinsic feature of the kernels and images. In this paper we propose a new model with super-sparse prior for the deblurring problem from one single image. Since the close-form formulation of this model doesn't exist, we use a look-up table trick to approximate the solution. Qualitative and quantitative evaluation demonstrate that our model with super-sparse prior can produce stable and high-quality results. © Springer-Verlag 2013.

关键词： Convolution

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Local linear spectral hashing

Local linear spectral hashing

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20th International Conference on Neural Information Processing, ICONIP 2013

作者： Zhao, Kang Liu, Dengxiang Lu, Hongtao MOE-Microsoft Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9783642420504

Hashing for large scale image retrieval has become more and more popular because of its improvement in computational speed and storage reduction. Spectral Hashing (SH) is a very efficient unsupervised hashing method through mapping similar images to similar binary codes. However, it doesn't take the non-neighbor points into consideration, and its assumption of uniform data distribution is usually not true. In this paper, we propose a local linear spectral hashing framework that minimizes the average Hamming distance with a new local neighbor matrix, which can guarantee the mapping not only from neighbor images to neighbor codes, but also from non-neighbor images to non-neighbor codes. Based on the framework, we utilize three linear methods to handle the proposed problem, including orthogonal hashing, non-orthogonal hashing, and sequential hashing. The experiments on two huge datasets demonstrate the efficiency and accuracy of our methods. © Springer-Verlag 2013.

关键词： Hamming distance

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Image classification based on weight adjustment before feature pooling

Image classification based on weight adjustment before featu...

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20th International Conference on Neural Information Processing, ICONIP 2013

作者： Feng, Shaokun Lu, Hongtao Huang, Lei MOE-Microsoft Laboratory for Intelligent Computing and Intelligent Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9783642420504

In image classification based on Bag-of-Features(BoF), the Locality-constrained Linear Coding (LLC) is a successful implementation, which is a more effective coding scheme compared with the traditional vector quantization(VQ) coding. Although, to achieve the best performance, max pooling scheme is chosen in the SPM layer, much of the spatial information is still lost during the pooling step, because all the coded descriptors are given the same importance to obtain the final representation. In this paper, we propose a new scheme that makes full use of spatial structure information to readjust their relative weights red and thus give some descriptors more chances to appear in the final feature vector more than others. Experiments of image classification on benchmark datasets show that the proposed method outperforms the LLC method. © Springer-Verlag 2013.

关键词： Image classification

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