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2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP)最新文献

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An improvement iterative approach for wideband digital predistortion using under-sampling 基于欠采样的宽带数字预失真改进迭代方法
2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP) Pub Date : 2014-07-09 DOI: 10.1109/ChinaSIP.2014.6889327
Lie Zhang, Yan Feng
{"title":"An improvement iterative approach for wideband digital predistortion using under-sampling","authors":"Lie Zhang, Yan Feng","doi":"10.1109/ChinaSIP.2014.6889327","DOIUrl":"https://doi.org/10.1109/ChinaSIP.2014.6889327","url":null,"abstract":"The performance of the traditional approach of wideband digital pre-distortion (DPD) of radio frequency (RF) power amplifier (PA) is subject to the analog to digital converter (ADC) sampling rate of transmitter. In this paper, an improvement DPD iterative approach is proposed. Firstly, DPD input signal and PA output signal are under-sampled by Zhu's generalized sampling theorem (ZGST). Secondly, an optimized iterative model is employed to obtain DPD model. The parameters of it can be extracted by DPD input signal and PA output signal. This improvement DPD iterative approach not only reduces hardware requirement of ADC sampling rate but also gives almost same linear performance with that by full sampling rate. The performance is validated by measurement result.","PeriodicalId":248977,"journal":{"name":"2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122400678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Single-layer Unsupervised Feature Learning with l2 regularized sparse filtering 基于l2正则化稀疏滤波的单层无监督特征学习
2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP) Pub Date : 2014-07-09 DOI: 10.1109/ChinaSIP.2014.6889288
Zhao Yang, Lianwen Jin, Dapeng Tao, Shuye Zhang, Xin Zhang
{"title":"Single-layer Unsupervised Feature Learning with l2 regularized sparse filtering","authors":"Zhao Yang, Lianwen Jin, Dapeng Tao, Shuye Zhang, Xin Zhang","doi":"10.1109/ChinaSIP.2014.6889288","DOIUrl":"https://doi.org/10.1109/ChinaSIP.2014.6889288","url":null,"abstract":"Patch-based Single-layer Unsupervised Feature Learning (SUFL) has been successfully applied in several tasks of computer vision. In the feature learning process, the key ingredient is how to learn a good feature mapping that connects patches to feature vectors. Among various feature mapping methods, the sparse filtering is easy to be implemented and hyper-parameter free. However, the standard sparse filtering method only considers the sparsity distribution of the learned features, ignoring the feature mapping matrix itself. This will lead to a random magnitude for mapping matrix and further weaken the generation performance. In this paper we proposed L2 regularized sparse filtering for the feature mapping in SULF. Classification experiments on three different datasets, i.e., CIFAR-10, small Norb, and subsets of CISIA-HWDB1.0 handwritten characters, show that our method has better performance comparing with the standard sparse filtering.","PeriodicalId":248977,"journal":{"name":"2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP)","volume":"30 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116335975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
Localization of gene expression regions in Drosophila embryonic images 果蝇胚胎图像中基因表达区的定位
2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP) Pub Date : 2014-07-09 DOI: 10.1109/ChinaSIP.2014.6889300
Qi Li, Wagner Silveira, Y. Gong
{"title":"Localization of gene expression regions in Drosophila embryonic images","authors":"Qi Li, Wagner Silveira, Y. Gong","doi":"10.1109/ChinaSIP.2014.6889300","DOIUrl":"https://doi.org/10.1109/ChinaSIP.2014.6889300","url":null,"abstract":"Automatic localization of gene expression regions in Drosophila embryonic images is an important step in a computational system for the discovery of patterns of gene-gene interaction. In this paper, we propose a thresholding framework that selects an optimal threshold via a consistency criterion on good candidate thresholds provided by multiple response functions, including intensity histograms. In experiments, we test the proposed framework, being compared with four well-known methods, on images in Berkley Drosophila Genome Project (BDGP) dataset, and obtain promising results.","PeriodicalId":248977,"journal":{"name":"2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115173063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Synthesis of room transfer function over a region of space by multiple measurements using a higher-order directional microphone 利用高阶定向传声器通过多次测量合成空间区域上的房间传递函数
2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP) Pub Date : 2014-07-09 DOI: 10.1109/ChinaSIP.2014.6889191
P. Samarasinghe, T. Abhayapala, M. Poletti
{"title":"Synthesis of room transfer function over a region of space by multiple measurements using a higher-order directional microphone","authors":"P. Samarasinghe, T. Abhayapala, M. Poletti","doi":"10.1109/ChinaSIP.2014.6889191","DOIUrl":"https://doi.org/10.1109/ChinaSIP.2014.6889191","url":null,"abstract":"Spatial sound field recording and reproduction in reverberant rooms require the measurement of room transfer functions (RTF) and corresponding compensation such as room equalization to avoid unintended effects. Typically, the RTF rapidly varies over the room and hence requires a large number of point to point measurements to characterize the room. This paper provides (i) an efficient parameterization of the three dimensional acoustic transfer function over a region of space and (ii) a method to merge distributed multiple measurements by a higher order microphone (such as a spherical array) to analyze and synthesize the room transfer function over a region of space. The proposed method is shown to be a practical way of measuring the RTF over large areas with a significantly reduced number of measurements and improved robustness.","PeriodicalId":248977,"journal":{"name":"2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123441090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
A Bayesian network viewon linear and nonlinear acoustic echo cancellation 基于贝叶斯网络的线性和非线性回声消除方法
2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP) Pub Date : 2014-07-09 DOI: 10.1109/ChinaSIP.2014.6889292
R. Maas, Christian Huemmer, A. Schwarz, Christian Hofmann, Walter Kellermann
{"title":"A Bayesian network viewon linear and nonlinear acoustic echo cancellation","authors":"R. Maas, Christian Huemmer, A. Schwarz, Christian Hofmann, Walter Kellermann","doi":"10.1109/ChinaSIP.2014.6889292","DOIUrl":"https://doi.org/10.1109/ChinaSIP.2014.6889292","url":null,"abstract":"In this contribution, we provide a new derivation of the normalized least mean square (NLMS) algorithm from a machine learning perspective. By applying the inference rules of Bayesian networks to a linear observation model, the NLMS can be shown to arise as a modification of the Kalman filter equations. Based on a nonlinear observation model, we exemplify the benefit of the Bayesian point of view by employing the technique of particle filtering to realize a tractable algorithm for nonlinear acoustic echo cancellation. Experiments carried out on real smartphone recordings reveal the remarkable performance of the new approach.","PeriodicalId":248977,"journal":{"name":"2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125258575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
A sidelobes/grating lobes suppression method for ultrawindeband ultrasparse array through-the-wall imaging radar 一种超波段超解析阵列穿壁成像雷达旁瓣/光栅瓣抑制方法
2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP) Pub Date : 2014-07-09 DOI: 10.1109/ChinaSIP.2014.6889231
Xin Tu, G. Zhu, Jun Hu, Xiaotao Huang, Zhimin Zhou
{"title":"A sidelobes/grating lobes suppression method for ultrawindeband ultrasparse array through-the-wall imaging radar","authors":"Xin Tu, G. Zhu, Jun Hu, Xiaotao Huang, Zhimin Zhou","doi":"10.1109/ChinaSIP.2014.6889231","DOIUrl":"https://doi.org/10.1109/ChinaSIP.2014.6889231","url":null,"abstract":"Ultrasparse array based through-the-wall imaging radars employing stepped frequency continuous wave are faced with high range sidelobes and lateral grating lobes. Range sidelobes are usually reduced by windowing at the expense of lower range resolution and stronger lateral grating lobes. Phase coherence factor (PCF) can suppress lateral grating lobes but fails to mitigate range sidelobes. If we weigh the windowed image by PCF to combat range sidelobes and lateral grating lobes, range windowing will raise the grating lobe level and thus degrade the PCF performance. To solve this problem, we propose a method based on PCF combined with dual apodization (DA), which can suppress both range sidelobes and lateral grating lobes efficiently. Simulation and experiment results demonstrate the validity of this method.","PeriodicalId":248977,"journal":{"name":"2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134474540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Recurrent Deep-Stacking Networks for sequence classification 用于序列分类的循环深度堆叠网络
2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP) Pub Date : 2014-07-09 DOI: 10.1109/ChinaSIP.2014.6889295
H. Palangi, L. Deng, R. Ward
{"title":"Recurrent Deep-Stacking Networks for sequence classification","authors":"H. Palangi, L. Deng, R. Ward","doi":"10.1109/ChinaSIP.2014.6889295","DOIUrl":"https://doi.org/10.1109/ChinaSIP.2014.6889295","url":null,"abstract":"Deep Stacking Networks (DSNs) are constructed by stacking shallow feed-forward neural networks on top of each other using concatenated features derived from the lower modules of the DSN and the raw input data. DSNs do not have recurrent connections, making them less effective to model and classify input data with temporal dependencies. In this paper, we embed recurrent connections into the DSN, giving rise to Recurrent Deep Stacking Networks (R-DSNs). Each module of the R-DSN consists of a special form of recurrent neural networks. Generalizing from the earlier DSN, the use of linearity in the output units of the R-DSN enables us to derive a closed form for computing the gradient of the cost function with respect to all network matrices without backpropagating errors. Each module in the R-DSN is initialized with an echo state network, where the input and recurrent weights are fixed to have the echo state property. Then all connection weights within the module are fine tuned using batch-mode gradient descent where the gradient takes an analytical form. Experiments are performed on the TIMIT dataset for frame-level phone state classification with 183 classes. The results show that the R-DSN gives higher classification accuracy over a single recurrent neural network without stacking.","PeriodicalId":248977,"journal":{"name":"2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131000931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
Imaging of missile-borne bistatic forward-looking SAR 弹载双基地前视SAR成像
2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP) Pub Date : 2014-07-09 DOI: 10.1109/ChinaSIP.2014.6889227
Ziqiang Meng, Yachao Li, M. Xing, Z. Bao
{"title":"Imaging of missile-borne bistatic forward-looking SAR","authors":"Ziqiang Meng, Yachao Li, M. Xing, Z. Bao","doi":"10.1109/ChinaSIP.2014.6889227","DOIUrl":"https://doi.org/10.1109/ChinaSIP.2014.6889227","url":null,"abstract":"As a special imaging mode, missile-borne bistatic forward-looking synthetic aperture radar (MBFL-SAR) has many advantages in two-dimensional (2-D) imaging capability for targets in the straight-ahead position over mono-static missile-borne SAR and airborne SAR. It is difficult to obtain the 2-D frequency spectrum of the target echo signal due to the high velocity and acceleration in this configuration, which brings a lot of obstacles to the following imaging processing. A new imaging algorithm for MBFL-SAR configuration based on series reversion is proposed in this paper. The 2-D frequency spectrum obtained through this method can implement range compression and range cell migration correction (RCMC) effectively. Finally, some simulations of point targets and comparison results confirm the efficiency of our proposed algorithm.","PeriodicalId":248977,"journal":{"name":"2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP)","volume":"382 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113967071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
3D human face modeling for facial animation using regional adaptation 基于区域适应的三维人脸动画建模
2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP) Pub Date : 2014-07-09 DOI: 10.1109/ChinaSIP.2014.6889271
Yanhui Huang, Yangyu Fan, Weihua Liu, Liangliang Wang
{"title":"3D human face modeling for facial animation using regional adaptation","authors":"Yanhui Huang, Yangyu Fan, Weihua Liu, Liangliang Wang","doi":"10.1109/ChinaSIP.2014.6889271","DOIUrl":"https://doi.org/10.1109/ChinaSIP.2014.6889271","url":null,"abstract":"This paper proposes an efficient method to reconstruct human face models from 3D face scans using an adaptation algorithm based on regional information. The resulting model can represent individual facial shapes with various expressions, establishing dense correspondences across the whole facial expression sequences. We first initialize the global shape of the face model by implementing RBF interpolation. An efficient vertex mapping is then developed to reconstruct the surface details. The new 3D face are finally created by remapping the scan texture to the facial surface. Experiments show that our method can create effective 3D face models for continuous and realistic 3D facial animation.","PeriodicalId":248977,"journal":{"name":"2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP)","volume":"193 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116396832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Sparsity-enabled signal transient feature extraction using wavelet basis and constrained optimization algorithm 基于小波基和约束优化算法的稀疏化信号瞬态特征提取
2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP) Pub Date : 2014-07-09 DOI: 10.1109/ChinaSIP.2014.6889351
Wei Fan, G. Cai, Weiguo Huang, Zhongkui Zhu
{"title":"Sparsity-enabled signal transient feature extraction using wavelet basis and constrained optimization algorithm","authors":"Wei Fan, G. Cai, Weiguo Huang, Zhongkui Zhu","doi":"10.1109/ChinaSIP.2014.6889351","DOIUrl":"https://doi.org/10.1109/ChinaSIP.2014.6889351","url":null,"abstract":"Ill-posed linear inverse problems (ILIP), such as restoration and reconstruction, are core topics of transient feature extraction in cyclostationary signal processing. A standard formulation for solving these problems consists of a constrained optimization problem with a regularization function minimized. In this paper, a method combining sparse representation and special wavelet basis is proposed to handle one class of constrained problems tailored to transient feature extraction applications. Simulation study concerning cyclic transients signal shows the effectiveness of this method. Application in transient feature extraction of fault gearbox vibration signal shows that the proposed method can extract the transient feature effectively.","PeriodicalId":248977,"journal":{"name":"2014 IEEE China Summit & International Conference on Signal and Information Processing (ChinaSIP)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128429659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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